Packaged goods inspection system and method

Abstract

An inspection device for inspecting boxed goods includes: at least one conveyor; at least one camera for capturing box image data of each boxed goods that is advanced through the inspection device using the at least one conveyor; and a processor configured to receive the box image data from the at least one camera. The processor is configured to characterize a box external protrusion of the boxed goods as a box flap in an open condition from the box image data, wherein the processor is configured to parse the box image data and determine that the box external protrusion is a consistent flat surface and is programmed with a parameter array of physical property parameters describing box flap consistency attributes that determine the consistent flat surface that defines an open box flap condition.

Description

[0001] Cross - Reference to Related Applications

[0002] This application is a non - provisional application of and claims the benefit of U.S. Provisional Patent Application No. 63 / 287,631, filed on Dec. 9, 2021, and U.S. Provisional Patent Application No. 63 / 138,946, filed on Jan. 19, 2021, the disclosures of which are incorporated herein by reference in their entireties. Technical Field

[0003] Aspects of the disclosed embodiments relate to product inspection and, in particular, to a system and method for inspecting packed goods. Background Art

[0004] There is a need to improve systems and methods for inspecting packed goods.

[0005] Typically, a packed - goods inspection system includes LED (light - emitting diode) array (curtain) illumination. The LEDs in these arrays have a relatively large spacing (greater than 5 mm) between them, so they only produce a “sampled” image rather than fully imaging the packed goods. Other methods use laser triangulation methods, which are fast, accurate, and robust, but are sensitive to reflective surfaces such as shrink wrap. Some packed - goods inspection systems employ image comparison to detect features of the packed goods (such as open flaps), where multiple images of the packed goods with known / predefined configurations are used for feature detection. Other packed - goods inspection systems use laser scanners to detect features of the packed goods (such as open flaps). Brief Description of the Drawings

[0006] The foregoing aspects and other features of the disclosed embodiments are explained in the following description in conjunction with the accompanying drawings, in which:

[0007] Figure 1 、 1A 、1B and 1C are schematic illustrations of a box inspection system according to aspects of the disclosed embodiments;

[0008] Figure 2A and 2B are schematic perspective views of an example of a product box inspected according to aspects of the disclosed embodiments;

[0009] Figure 3 is a schematic diagram illustrating a process flow chart of a product detection process according to aspects of the disclosed embodiments;

[0010] Figure 4 is a view illustrating a generally acquired image without a product as seen by a camera vision system according to aspects of the disclosed embodiments;

[0011] Figure 5 is a diagram showing a region of interest analyzed from a general image illustrated in Figure 4 ;

[0012] Figure 6 is a diagram showing an enlarged view of an analyzed region from Figure 5 ;

[0013] Figure 7 is a schematic diagram showing a process flow chart of product measurement according to aspects of the disclosed embodiments;

[0014] Figure 8 shows, in side view and top view, a schematic diagram of product measurement results obtained through the process of Figure 3 and 7 according to aspects of the disclosed embodiments;

[0015] Figure 9 , 9A , 9B, and 9C show, in side view and top view, a schematic diagram of the actual box product measurement obtained through the process of Figure 3 and 7 according to aspects of the disclosed embodiments;

[0016] Figure 10 shows, in side view and top view, a schematic diagram of external box product measurement obtained through the process of Figure 3 and 7 according to aspects of the disclosed embodiments;

[0017] Figure 11 shows, in side view and top view, a schematic diagram of the maximum bulge measurement obtained through the process of Figure 3 and 7 according to aspects of the disclosed embodiments, and Figure 11A , 11B , and 11C are other schematic illustrative examples of bulges on one or more sides of the product according to aspects of the disclosed embodiments;

[0018] Figure 12 is a diagram showing the detection of the presence of debris on the camera system window according to aspects of the disclosed embodiments;

[0019] Figure 13A - 13F is an exemplary schematic illustration showing a packed cargo with an open flap according to aspects of the disclosed embodiments;

[0020] Figure 14A - 14Dis an exemplary schematic illustration of case image data obtained by a case inspection system utilizing Figure 1 and 1A at -1°C;

[0021] Figures 15 - 20 schematically illustrates example parameters employed by a case inspection system utilizing Figure 1 and 1A at -1°C for open flap determination;

[0022] Figure 21 is a schematic illustration of the operation of a case inspection system utilizing Figure 1 and 1A at -1°C, in accordance with aspects of the disclosed embodiments;

[0023] Figure 22 is an exemplary flowchart of a method(s) in accordance with aspects of the disclosed embodiments;

[0024] Figure 23A is a schematic perspective illustration of image data obtained by a case inspection system utilizing Figure 1 and 1A at -1°C, showing case goods having a concave surface;

[0025] Figure 23B is an exemplary schematic illustration of case image data obtained by a case inspection system utilizing Figure 1 and 1A at -1°C (corresponding to the concave surface of Figure 23A );

[0026] Figure 23C is a schematic perspective illustration of a combination of case goods having case goods characteristics (which may affect case goods handling, storage, and transportation), in accordance with aspects of the disclosed embodiments;

[0027] Figure 24A is a perspective illustration of case goods image data obtained by a case inspection system utilizing Figure 1 and 1A at -1°C, showing a protrusion on the top surface of the case goods;

[0028] Figure 24B is an exemplary schematic side illustration of case goods image data having a protrusion on the bottom surface of the case goods, in accordance with aspects of the disclosed embodiments;

[0029] Figure 25 and 25Ais a schematic illustration of packed cargo data obtained using a Figure 1 and 1A -1C case inspection system, showing a side view of packed cargo having one or more tapers or narrowing on one or more sides of the packed cargo;

[0030] Figure 26 is a schematic illustration of packed cargo data obtained using a Figure 1 and 1A -1C case inspection system, showing a side view of packed cargo having more than one product therein;

[0031] Figure 27 is a schematic illustration of packed cargo data obtained using a Figure 1 and 1A -1C case inspection system, showing a side view of packed cargo having one or more tapers on one or more sides of the packed cargo;

[0032] Figure 28A and Figure 28B is a schematic top and side illustration of expected packed cargo dimensions according to aspects of the disclosed embodiments;

[0033] Figure 29 is a schematic top view illustration of a plurality of packed cargoes traveling side by side generally along a conveyor; and

[0034] Figure 30 is an exemplary flowchart of a (one or more) method according to aspects of the disclosed embodiments. DETAILED DESCRIPTION

[0035] Note that throughout the figures, like features have like reference numerals. Also note that references herein to the "top" and "bottom" qualifiers (and other spatial qualifiers) refer only to the orientation of the figures as presented in this application and do not imply any absolute spatial orientation.

[0036] Figure 1 Illustrated is an exemplary packed cargo inspection system 100 according to aspects of the disclosed embodiments. Although aspects of the disclosed embodiments will be described with reference to the figures, it should be understood that aspects of the disclosed embodiments may be embodied in many forms. Additionally, any suitable size, shape, or type of component or material may be used.

[0037] An example of a (one or more) case goods handled by the case goods inspection system 100 is a shrink-wrapped product 200, which includes a product container included in the shrink wrap, or an array of one or more product containers, or a (one or more) product, as Figure 2A illustrated in. Another example of a (one or more) case goods is a boxed product 210 (such as a cardboard box or other suitable shipping container), as Figure 2B illustrated in, which encloses a product container, or an array of one or more product containers, or a (one or more) containerless product. The term "product" should be understood herein to include any type of (one or more) consumer product in any type of packaging, such as but not limited to sealed cartons, tote bags, open-top cartons, trays with or without shrink wrap film, bags, and pouches, etc. (i.e., the terms "product" and case goods include the shrink-wrapped product 200 and the boxed product 210). The dimensions of the (one or more) products / (one or more) cases 102 (e.g., input products) received by the case goods inspection system 100 (generally referred to herein as products or case goods) can vary greatly between different types of products. For illustrative purposes only, typical dimensions (W×L×H) can be between approximately 4 in × 4 in × 2 in (approximately 10 cm × 10 cm × 5 cm) and approximately 25 in × 30 in × 30 in (approximately 63 cm × 76 cm × 76 cm). Although Figure 2A and 2B the examples in are illustrated as having a generally hexahedral shape, the (one or more) products and / or product cases can have any desired three-dimensional shape, such as cylindrical, curved, conical, ovoid, etc., and one or more surfaces of any side can be curved or inclined relative to another surface on the other side or the same side. As will be described in more detail below, one or more of the products 102 include flaps that can be folded to close the opening of the product container. Aspects of the disclosed embodiments provide at least detection of these flaps, where the flaps are in an open or partially open configuration.

[0038] The case goods inspection system or apparatus 100 includes at least one input conveyor 110, at least one output conveyor 120, a vision system 150, a controller 199, and a user interface 198 (see Figures 8 - 12Exemplary user interface 198 output). The case goods inspection system 100 forms (at least in part forms) the inbound conveyor system 195 or is otherwise included in the inbound conveyor system 195 for guiding the case goods 102 into the logistics facility 190, wherein at least one of the conveyors 110, 120 is configured to advance the case goods 102 into the logistics facility 190. For illustrative purposes only, the case goods inspection system 100 communicates with at least one of the conveyors 110, 120 and receives the case goods 102, which individually arrive at the input conveyor 110 in any orientation and position, and wherein the case goods 102 are transferred from the input conveyor 110 to the output conveyor 120 as described herein. The output of the case goods inspection system 100 includes various (quantitative) measurements that characterize each case goods, such as a box of goods. Examples of quantitative measurements include: "true box", "maximum box", "maximum bulge", "orientation angle", "distance from one side of the conveyor", open flap, indentation (e.g., inward bulge), etc.

[0039] At least one input conveyor 110 is configured to advance the case goods 102 through the case goods inspection system 100 (also referred to herein as "case goods inspection device 100"). For example, at least one input conveyor 110 is one or more of a conveyor belt (e.g., a top pad high grip conveyor), a roller conveyor, or any other suitable product conveying tool configured to transport the incoming case goods 102 from any suitable device (e.g., automated or otherwise) or a warehouse worker (e.g., human). At least one input conveyor 110 is configured to move the case goods 102 into and through the vision system 150 with minimized vibration and slippage (e.g., the vibration and slippage are below any suitable predetermined threshold for vibration and slippage, which may depend on the resolution of the vision system 150 components). At least one output conveyor 120 is generally similar to at least one input conveyor 110 and transports the case goods 102 away from the vision systems 150, 170 to any suitable destination, including suitable product handling equipment located downstream of the case goods inspection system 100 or after it in process terms.

[0040] Reference Figure 1 and 1A-1C, the vision system 150 is at least partially positioned (e.g., mounted) around and adjacent to the conveyors 110 and / or 120 for viewing and measuring the characteristics of the packed goods 102 (as described above) that are advanced through the packed goods inspection system 100 by the conveyor(s) 110, 120. As described herein, the vision system 150 includes at least one camera (such as, for example, at least one sensor / imaging device 171 - 173), which is arranged to capture bin image data of each packed goods 102 that is advanced through the packed goods inspection system 100 by at least one input conveyor 110.

[0041] According to aspects of the disclosed embodiments, the vision system 150 at least includes a flap detection system 170 (also referred to herein as the "imaging system" or "detection system"), and the flap detection system 170 includes at least one sensor / imaging device 171 - 173 (referred to herein as sensors 171 - 173) for detecting open flaps (or otherwise achieving detection of open flaps), protrusions, and / or depressions of the packed goods 102. The sensor is any suitable sensor configured to detect / sense at least the flaps, protrusions, and / or depressions of the packed goods 102, and includes but is not limited to cameras (only three are illustrated for exemplary purposes, and it should be understood that there may be more or fewer than three cameras), laser detection systems, or any other suitable optical or acoustic detection systems for detecting the flaps of the packed goods 102. The sensors 171 - 173 can be any suitable cameras, such as, for example, 3D cameras, including but not limited to time-of-flight cameras or any suitable 3D imaging cameras. In one or more aspects of the disclosed embodiments, the sensors 171 - 173 are positioned adjacent to one or more of the conveyors 110, 120 for detecting open flaps, protrusions, and / or depressions of the packed goods 102, as will be described in more detail below. As Figures 1A - 1C seen, in one or more aspects of the disclosed embodiments, the flap detection system 170 includes lasers, where each sensor 171 - 172 (only two cameras are illustrated in Figures 1A - 1C for exemplary purposes, and it should be understood that more or fewer than two cameras may be provided) is paired with lasers 172L, 173L (note that sensor 171 can also be paired with laser 171L, which is not illustrated in Figures 1A - 1CIn the (China). Lasers 171L, 172L, 173L are configured to emit illumination sheets that provide corresponding scan lines on the cased goods 102, where the scan lines illuminate the contour of the cased goods 102. In one or more aspects, the illumination of the contour by the scan lines facilitates the detection of open flaps, protrusions, and / or depressions of the cased goods 102 (e.g., through image identification of bin image data from sensors 172, 173). In still other aspects, one or more of sensors 171 - 173 are paired with corresponding lasers, while one or more of the other sensors 171 - 173 do not have an associated laser. In one or more aspects, lasers 171L, 172L, 173L are generally similar to light sources 182, 183 described herein.

[0042] Vision system 150 may further include another imaging system (e.g., contour detection system 180, also referred to as a bin inspection system or station), which is separate from and different from at least one of sensors 171 - 173 of flap detection system 170. Contour detection system 180 images the cased goods 102, which is separate from and different from imaging the cased goods 102 by at least one of sensors 171 - 173, for inspection of the cased goods other than for detection of depression conditions. Contour detection system 180 may be generally similar to U.S. Patent Application No. 15 / 416,922, filed on January 26, 2017 (and entitled "Cased Goods Inspection System and Method", now U.S. Patent No. _________), the disclosure of which is incorporated herein by reference in its entirety.

[0043] The profile detection system 180 includes at least one sensor / imaging device 181, 184, which are positioned adjacent to one or more of the conveyors 110, 120 and are configured to detect / sense the top and side profiles of the product 102. At least one sensor / imaging device 181, 184 of the profile detection system 180 is configured to capture an image of the shadow of each packed item 102 being advanced through the case inspection station 100, as described herein. The at least one sensor(s) 181, 184 of the profile detection system 180 are separate and different from the flap detection system 170, and the profile detection system 180 images the packed item 102, which is separate and different from the at least one sensor 171 - 173 of the flap detection system 170, for inspection of the packed item 102 other than the detection of open case flaps. Here, the profile detection system 180 images the packed item 102 for verification by the controller 199 / processor 199P of the identification of each packed item 102 (e.g., having a predetermined or expected identification of each packed item) and the conformity of each packed item 102 with the (e.g., predetermined or expected) case size parameters of the verified packed item 102.

[0044] According to aspects of the disclosed embodiments, the profile detection system 180 includes a first light source 182 that emits a first sheet of light, e.g., a continuous plane of substantially parallel / collimated light, within a small gap GP between the conveyors 110 and 120. For example, the first light source 182 may be located above the conveyors 110, 120 (as otherwise shown in Figure 1 ), or below the conveyors 110, 120. In one or more aspects, the first light source 182 may be common to both the profile detection system 180 and the flap detection system 170 (i.e., shared between the two) (e.g., the first light source may be used as one of the lasers 172L, 173L described above, or vice versa).

[0045] The profile detection system 180 further includes a first camera system 184, which is positioned, for example, opposite the first light source 182 with respect to the conveyors 110, 120. The first camera system 184 is positioned to receive the parallel / collimated light emitted by the first light source 182 that passes through, for example, the gap GP. For example, when the first light source 182 is located above the conveyors 110, 120, the first camera system 184 is located below the conveyors 110 and 120. In other aspects, the orientation of the first light source 182 and the first camera system 184 may be rotated about an axis defined by the direction of travel of the conveyors 110, 120, as desired, so as to maintain the relationship between the light source 182 (e.g., the light emitter) and the camera system 184 (e.g., the light receiver).

[0046] The second light source 183 emits a second sheet of light, i.e., a continuous plane of substantially parallel / collimated light, over a small gap between conveyors 110 and 120. For example, the second light source 183 may be located on one side of conveyors 110, 120 (the transmission of the parallel / collimated light beam of the second sheet being substantially orthogonal to the continuous plane of the parallel / collimated light of the first sheet). In one or more aspects, the second light source 183 may be common to (i.e., shared between) both the profile detection system 180 and the flap detection system 170 (e.g., the second light source may be used as one of the lasers 172L, 173L described above, or vice versa).

[0047] The second camera system 181 is positioned relative to conveyors 110, 120 accordingly (e.g., opposite the second light source 183) to receive illumination from the second light source 183. The second camera system 181 is positioned to receive the parallel / collimated light emitted by the second light source 183. For example, when the second light source 183 is located on one side of conveyors 110, 120, the second camera system 181 is located on the other opposite side of conveyors 110, 120.

[0048] According to one or more aspects of the disclosed embodiments, at least one of the light sources 182 or 183 may include a light shaper LS made of a lens or a mirror, which forms a collimated output beam. The light source is any suitable light source and may include, but is not limited to, one or more of the following: lasers, light-emitting diodes (LEDs), gas lamps, and any other electromagnetic radiation device suitable for electromagnetic illumination of a target object, the reflection or transmission of which can be captured by a suitable imaging system that generates an image or a pseudo-image of the illuminated target object.

[0049] The (one or more) collimated output beams of the light sources 182, 183 provide one or more sheets of parallel-propagating light that, when obstructed by the stowed cargo 102, project orthographic projection shadows onto the input windows of the corresponding camera systems 184, 181 opposite the corresponding light sources 182, 183. In this regard, the camera systems 184, 181 receive the incident collimated input beams output by the corresponding light sources.

[0050] In the illustrated example, both camera systems 184, 181 include at least one camera 181C, 184C. Camera systems 184, 181 may also include mirrors 181M, 184M and diffuser screens 181D, 184D (referred to as diffusers in the drawings). Mirrors 181M, 184M are employed, for example, to redirect the sheet of light parallel to conveyors 110, 120 to reduce the footprint of the overall case inspection system. Diffuser screens 181D, 184D (which may be any suitable type of illumination diffuser) are examples of input beam shapers that spread the input beam by diffusing the parallel light incident thereon from corresponding light sources 182, 183 such that corresponding cameras 184, 181 (e.g., camera imaging arrays having a desired predetermined width structurally or defined by any suitable controller such as controller 199 such that the array) can capture and digitize the diffused light from the full width of the corresponding sheet of light emitted by light sources 182, 183. As can be appreciated, (one or more) cameras 184, 181 can image (one or more) cases and / or products within the full width of the sheet of light (as can further be appreciated, the full width can span the lateral boundaries of conveyors 110, 120 and the height H of inspection system opening 101).

[0051] To reduce the light footprint or to be able to use a lower power laser-like light source with respect to the flap detection system 170 and the profile detection system 180, a smaller sheet of parallel light can be used that has an overlap to maintain continuity and cover a larger surface. Any suitable calibration process can be used to realign these separate sheets into a single sheet via, for example, the software of controller 199.

[0052] As described herein, at least one sensor / imaging device 171 - 173 of the flap detection system 170 is connected to case inspection station 100 and is separate and distinct from at least one camera 181, 184. At least one sensor / imaging device 171 - 173 is arranged to capture case image data 1400 of each packed cargo 102 advanced through case inspection station 100 in addition to the case image data captured by at least one camera 181, 184. In Figure 1 and 1AIn the example illustrated in -1C, the flap detection system 170 utilizes bin image data from the contour detection system 180 or any other suitable data, as described in more detail herein. Here, the flap detection system 170 is located downstream, which is relative to the product travel direction along the conveyor(s) 110, 120 from the contour detection system 180 (e.g., the product 120 passes through the contour detection system 180 before passing through the flap detection system 170); however, in other aspects, the flap detection system 170 can be located upstream of the contour detection system 180. The relative positioning of the flap detection system 170 and the contour detection system 180 enables the flap detection system 170 to image one or more outer sides of the packed goods 102 substantially simultaneously with the contour detection system 180 imaging the packed goods 102 (in one or more aspects, all visible outer sides are not sitting against the conveyor(s) 110, 120, for example), as will be described herein.

[0053] Reference Figure 1 , the flap detection system 170 includes one or more platforms, struts, or other suitable supports that are positioned adjacent to the conveyor(s) 110, 120, and the sensors / imaging devices 171 - 173 (and in one or more aspects are lasers 171L - 173L) are located thereon. Again note that while three sensors 171 - 173 are illustrated in Figure 1 but in other aspects, more or fewer than three sensors (such as, for example, the two sensors illustrated in Figures 1A - 1C ) can be arranged to image all five visible outer sides of the packed goods 102 that are not sitting against the conveyor(s) 110, 120. As the product passes through the flap detection system 170, the sensors / imaging devices 171 - 173 are arranged relative to the conveyors 110, 120 to image any suitable number of surfaces of each packed goods 102; however, in other aspects, a single sensor / imaging device with suitable prisms or mirrors can also provide images of a suitable number of surfaces of each packed goods 102.

[0054] In Figure 1 , the sensors 171 - 173 are arranged such that each sensor 171 - 173 images at least one or more corresponding outer sides of the packed goods 102. For example, sensor 171 images the lateral sides (and the contours of the longitudinal and top sides) of the packed goods 102, sensor 173 images the top (and the contours of the lateral and longitudinal sides) of the packed goods 102, and sensor 172 is angled to image the lateral, top, and longitudinal sides of the packed goods 102. In Figures 1A - 1CIn [the context], sensors 172 and 173 are adjusted at an angle relative to each other and are disposed on opposite sides of the conveyor(s) 110, 120 to image two lateral sides, two longitudinal sides, and the top of the case goods 102 (e.g., these two sensors image five visible sides of the case goods 102). In some aspects of the disclosed embodiments, the flap detection system is provided with any suitable illumination (e.g., such as the laser / collimated light source described above), which facilitates imaging of the case goods 102 moving along the conveyors 110, 120. In one aspect, the exposure (e.g., ISO and / or shutter speed) of the sensors / imaging devices 171 - 173 is such that the case goods 102 moving along the conveyors 110, 120 appear stationary and the resulting images of the case goods 102 moving along the conveyor are not blurred; while in other aspects, a "stop - motion effect" of the case goods 102 moving along the conveyors 110, 120 can be created by any suitable flash illumination.

[0055] As described above, the sensors / imaging devices 171 - 173 are any suitable sensors / imaging devices, such as, for example, a time - of - flight camera or any other suitable imager that is capable of generating, for example, a three - dimensional depth map or a point cloud of each case goods 102 traveling along the conveyors 110, 120. In Figure 1 [the context], the sensor / imaging device 172 is positioned adjacent to the conveyors 110, 120 to image at least the leading side 102F of the case goods 102 (e.g., the leading side 102F is the front or longitudinal side of each case goods 102 relative to the direction of travel along the conveyors 110, 120 - note that the term "front" is used herein for exemplary purposes only and any spatial term can be used). For example, the sensor / imaging device 172 is mounted to the support post 170M in any suitable manner to face generally opposite to the direction of travel along the conveyors 110, 120 so as to image the case goods 102 traveling towards the sensor / imaging device 172. The sensor / imaging device 173 is also mounted on the support post 170M and is positioned above the conveyors 110, 120 to image a plan view of at least the top side 102T of the case goods 102 traveling along the conveyors 110, 120 (e.g., the "top" side is relative to the side of the case goods 102 sitting on the conveyors 110, 120 - note that the term "top" is used herein for exemplary purposes only and any spatial term can be used). The sensor / imaging device 171 is mounted on any suitable surface adjacent to the conveyors 110, 120 to image the lateral side 102L of the case goods 102 traveling along the conveyors 110, 120. Referring to Figures 1A - 1C , the sensor 172 is mounted (in a similar manner toFigure 1 in a manner such that it is positioned relative to the conveyor(s) 110, 120 for imaging a perspective view of the case goods 102 that includes a lateral side 102L1, a top side 102T, and a trailing or “rear” longitudinal side 102R of the case goods 102. The sensor 173 is mounted (in a manner similar to Figure 1 in a manner such that it is positioned relative to the conveyor(s) 110, 120 for imaging a perspective view of the case goods 102 that includes an opposite lateral side 102L2, a top side 102T, and a leading or front longitudinal side 102F of the case goods 102. Each of the sensors / imaging devices 171 - 173 is positioned to produce an image of at least one corresponding side of the case goods 102, and as can be appreciated, the number of cameras can depend on the particular case goods being inspected.

[0056] As described herein, at least one camera (e.g., sensors / imaging devices 171 - 173) is arranged to image each exposed case side 102T, 102F, 102R, 102L1, 102L2 of each case goods 102 being advanced through the inspection device 100 by at least one conveyor 110, 120, to image at least one of a case side indentation condition (or inward variation) and an external case protrusion that is apparent on each imaged case side 102T, 102F, 102R, 102L1, 102L2 from a common image of each imaged case side 102T, 102F, 102R, 102L1, 102L2. At least one sensor / imaging device 171 - 173 is arranged to capture case image data 1400 of each case goods 102 being advanced through the inspection device 100 by at least one conveyor 110, 120 such that the case image data represents at least one of a case side indentation 2300 (also referred to herein as an inward variation - see, e.g., Figure 23A ) and an external case protrusion 220, where at least one of the case side indentation 2300 and the external case protrusion 220 is apparent on at least one exposed case side 102F, 102R, 102T, 102L1, 102L2, and at least one exposed case side 102F, 102R, 102T, 102L1, 102L2 is provided in each exposed case side orientation of the case goods 102.

[0057] In other aspects, at least one sensor / imaging device 171 - 173 is arranged to capture bin image data 1400 of each packed cargo 102 that is advanced through inspection equipment 100 by at least one conveyor 110, 120, such that the bin image data 1400 represents a dented condition (or inward variation condition), where the dented condition is apparent on at least one exposed bin side 102T, 102L, 102F, 102R (and in some aspects, as described herein, on the bottom 102B), and at least one exposed bin side is provided in each exposed bin side orientation of the packed cargo 102. In addition to or in lieu of bin exterior protrusion determination, at least one exposed bin side 102T, 102L, 102F, 102R imaged by at least one sensor / imaging device 171 - 173 is arranged such that the dented condition (which is resolved from the dented condition apparent on the at least one imaged exposed bin side 102T, 102L, 102R, 102F) extends from the at least one exposed bin side 102T, 102L, 102R, 102F adjacent to the conveyor seat surfaces 110S, 120S on which the packed cargo 102 is seated.

[0058] The packed cargo inspection system 100 includes any suitable controller 199 (which includes any suitable processor 199P such that a reference to the controller 199 performing or being configured to perform the tasks / functions described herein implies operation of the processor 199P) or any other device or system (local or remote) that includes a computer-readable medium having non-transitory computer program code stored thereon that configures the controller 199 to record and analyze bin image data from the vision system 150 to calculate desired measurements or other suitable characteristics of the packed cargo 102 (as described herein). The controller 199 is operably coupled to at least one conveyor 110, 120 and communicatively coupled in any suitable manner to at least one sensor 171 - 173, 181, 184 of the vision system 150, such as via any suitable wired or wireless connection, to receive bin image data from at least one sensor 171 - 173 (see Figure 14A - 1 4H, regarding exemplary bin image data 1400 from sensors 171 - 173), 181, 184 (see Figure 5 、 6 and 8 - 11, regarding exemplary bin image data from sensors 181, 184).

[0059] Note that the controller 199 (e.g., via the processor 199P) is configured such that the inspection of the stowed goods based on the stowed goods image from the profile detection system 180 is resolved, which is separated from and different from the bin image data 1400 from at least one sensor 171 - 173 of the flap detection system 170 (see Figure 14A - 14D ) to resolve at least one of a bin side dent (also referred to as a bin side dent condition) and an open bin flap. The controller 199 is also arranged to determine any bin side dent 2300 and any bin external protrusion 220 of the stowed goods 102 from the imaging data of the profile detection system 180 that is separated from and different from the bin image data 1400 captured by at least one sensor 171 - 173 of the bin detection system 170 (see Figure 2A and 2B as well as Figures 9 - 11 ); and to resolve at least one of the bin side dent and the bin external protrusion 220 as a corresponding bin side dent and an open bin flap from the bin image data 1400 of at least one sensor 171 - 173 of the flap detection system 170 that is separated from and different from the image of the profile detection system 180. In one or more aspects, the controller 199 is configured to: independently of the image of the stowed goods 102 captured by the profile detection system 180, determine the presence of at least one of a bin side dent and a bin external protrusion 220 from the bin image data 1400 captured by at least one sensor 171 - 173 of the flap detection system 170.

[0060] In one or more aspects, the controller 199 is configured to: from the bin image data 1400 generated from a common image of the stowed goods 102 captured by at least one sensor 171 - 173 (see Figure 23B and 23C —e.g., a common image of one of at least one sensor 171 - 173 or a combined image from more than one of at least one sensor 171 - 173), the bin side dent 2300 of the stowed goods 102 (see Figure 23A, at least one of the box flaps characterized as being in an open condition (as will be described hereinafter) and the box exterior protrusions 220. Here, at least one of the exposed box sides 102F, 102R, 102T, 102L1, 102L2 imaged by at least one of the sensors 171 - 173 is arranged such that at least one of the box side depressions 2300 and the box flaps in an open condition (which is resolved from at least one of the box side depressions 2300 and the box exterior protrusions 220 that are apparent on the imaged at least one exposed box side 102F, 102R, 102T, 102L1, 102L2) extends from the at least one exposed box side 102F, 102R, 102T, 102L1, 102L2 and is adjacent to the conveyor seat surfaces 110S, 120S on which the packed goods 102 are seated ( Figure 1 ).

[0061] When the processor is configured to characterize at least one box top 102T or at least one box side 102L, 102R, 102F having a depressed condition from the box image data 1400 of the packed goods captured by at least one of the sensors 171 - 173, the processor 199P is programmed to resolve from the image data 1400 the inward variation (or depression) of at least one box top 102T or at least one box side 102L, 102R, 102F with respect to the predetermined planar consistency characteristic of the box top 102T or the box side 102L, 102R, 102F (e.g., such as from the expected box dimensions and box goods type, e.g., stock - keeping unit (SKU), as described herein). The processor 199P is configured to determine from the image data 1400, for the presence of each resolved inward variation, the physical characteristics that describe the depressed condition of at least one box top 102T or at least one box side 102L, 102R, 102F.

[0062] Reference Figure 3 , the operation of the packed goods inspection system 100 will be described. The packed goods 102 arrive on the conveyor 110 in any orientation and position. In one or more aspects, the position of the packed goods 102 on the conveyor 110 includes the distance or clearance from one side of the conveyor 110. Figure 3 Illustrates the product measurement process. The profile detection system 180 performs repeated image acquisitions into an image buffer (such as the image buffer of the controller 199 processor 199P) ( Figure 3 , block 310), triggered, for example, by an input conveyor encoder or alternatively by a stepper motor drive circuit that advances at least one of the conveyors 110 and 120.

[0063] Figure 4Illustrated is a representative example of what can be referred to as the original acquired image, which is acquired with a given encoder index value (using the imagers of the cameras of camera systems 181, 184), such an image being generated, for example, for four light sources (e.g., as can be used in any of light sources 182, 183) and one camera system implementation (e.g., (one or more) camera systems 184, 181). The image includes sub-regions 4GI, 4GV of irradiated and non-irradiated (non-exposed) pixels. The image analysis computer program algorithm does not consider the complete capture region of the camera image sensor where pixels are not exposed. Instead, a specific sub-region 4GI is considered, for example having a height 4H of 3 pixels and a full light sheet width 4W. Figure 5 Illustrated is the considered region 5GI (such as can correspond to such a light source), which is identified by a dashed rectangle representing the recorded image sub-region 5L and is processed by the image analyzer. Figure 6 Shown is a detail of a specific region 6GI, which is magnified to better illustrate the region considered by the image analysis algorithm.

[0064] For each acquired image ( Figure 4 ), the image analysis algorithm compares the pixel light intensity of the pixels in the specific region 5h ( Figure 5 ) to be analyzed with the normalized intensity value obtained from comparable sub-region samples (e.g., from 10 original baseline sample images) ( Figure 3 , block 320). Referring to Figure 3 , the normalized baseline can be a rolling baseline, where at each image acquisition step 320 (where there is no potential detection as will be described), the oldest image in the sample is deleted or erased from the record and replaced by the newly acquired original image ( Figure 3 , block 322). The number of images used in the baseline sample can be modified. The normalized intensity value can represent the ambient lighting level, for example taking into account changes in the lighting conditions in the surroundings of the packed goods inspection system and the presence of dust, liquid residues or small debris on the optical receiver.

[0065] For illustrative purposes, using the images acquired from the camera system 184 located below conveyors 110 and 120, the controller 199 verifies ( Figure 3, whether a plurality of pixels in the considered portion of the acquired image (recorded by at least one camera, or if desired, by two cameras 184, 181) have an intensity drop of more than, for example, about 40% (compared to the normalized intensity value), and represent a width of, for example, about 30 mm (about 1.2 in) or greater relative to the full width of the illumination sheet captured by the acquired image. As can be appreciated, the width, referred to herein as the threshold width of the reduced intensity portion of the acquired image, can be set as desired based on environmental conditions. The reduced intensity width of the image portion corresponds to and is attributable to a spatial intensity reduction caused by the disruption and / or occlusion or blocking of at least a portion of the (one or more) input light beams forming the illumination sheet that persists during the duration of the (one or more) acquired images, the disruption and / or obstruction or blocking being caused by, for example, an object that can be opaque or translucent and thus partially pass through the light beam / sheet. In other words, the passage of the product, case, and / or packaging through the sheet creates content that can also be referred to as a grayscale image for at least a portion of the width of the acquired image. If this is the case, the controller considers the potential detection of a product or packed goods ( Figure 3 , block 332). The thresholds for intensity drop (both the threshold width and the threshold intensity variation) can be modified as desired (e.g., the intensity drop threshold can be a drop of about 10% from a standard value). As can be appreciated, the two threshold settings determine the portion of the opaque or translucent material in the illumination sheet whose disruption creates the grayscale image, where this material is detectable and measurable, as will be further described (and the threshold width can be about 5 mm or about 0.2 in). In contrast, a completely opaque material will reflect, resulting in a substantially complete occlusion of the illumination and thus a corresponding portion of the graphic projection image.

[0066] The above process steps (e.g., Figure 3 , blocks 310 - 332) are repeated ( Figure 3 , block 334) as long as a plurality of pixels of a given acquired image have an intensity drop greater than a predetermined threshold intensity drop (which can also be expressed as an absolute intensity value threshold) (e.g., about 40%) and represent a width greater than a predetermined threshold width of about 30 mm (about 1.2 in) or greater, and the process stops when this condition is no longer true. While this first condition is true (established by exceeding two thresholds), if a plurality of images satisfying this condition represent a potential product length of about 60 mm (about 2.4 in) (as can be determined by an appropriate encoder that synchronizes the capture rate, identifies the conveyor displacement and rate (e.g., the conveyor advancement rate) in relation to or proportional to the acquired image and / or image frame), the controller considers that the packed goods 102 have been detected, or in other words, confirms that the detection is true.Figure 3 , the potential packing length for packing goods confirmation (for the box 336) can be set larger or smaller, such as a displacement of about 10 mm (about 0.4 in). In this case, the controller 199 combines the following images from the two camera systems 181 and 184 (using the combiner 199PC of the processor 199P( Figure 1 )): the previously acquired upstream image in front of the image of the detected packing goods 102, which represents a conveyor displacement of, for example, about 60 mm (about 2.4 in) (the representative length can be larger or smaller, for example, about 10 mm or about 0.4 in); the multiple images in which the packing goods 102 are detected; and the subsequently acquired downstream image after the detection of the packing goods 102 is asserted, which represents a conveyor displacement of, for example, about 60 mm (about 2.4 in), so as to construct ( Figure 3 , box 340) a composite continuous complete combined image of the packing goods 102, and this combined image can vary and does not need to be symmetric. If multiple images that meet the first and second conditions (i.e., the thresholds and durations 330, 336) represent a potential product with a width / length less than, for example, about 60 mm (about 2.4 in), the controller asserts that this detection ( Figure 3 , box 337) is a false detection, or the detected packing goods 102 are below the minimum acceptable length / width for the image acquisition process to continue normally. The system is robust against noise or parasitic signals (such as falling debris).

[0067] As described above, although two conditions are asserted, the successive construction of the combined image (or pseudo-image) of the scanned stowed goods 102 continues beyond, for example, about 60 mm (about 2.4 in) until the maximum acceptable product size is reached. In other words, when the controller 199 determines that the (one or more) acquired images of, for example, the camera system 184 (corresponding to the desired conveyor travel, for example, about 60 mm or 2.4 in) (if there are two cameras 184, 181, this determination may be influenced by the acquired images) no longer meet the above threshold (e.g., the considered portion of the acquired image does not have both a width or intensity drop greater than a set threshold (e.g., about 30 mm (1.2 in), about 40% drop)), the controller 199 records the accepted stowed goods size (such as from the recorded conveyor displacement, which is from an encoder that corresponds to image acquisition that exceeds the threshold). Thus, after the maximum acceptable product size is exceeded, the controller 199 (via appropriate programming) can continue the original image acquisition for combining into the combined image of the scanned stowed goods for an additional, for example, about 60 mm (about 2.4 in). It is to be understood that the "combined image" (or pseudo-image) and the "combined product image" correspond to the relative position and orientation of the illumination source and include images of the substantially orthogonal sides of the stowed goods, such as side view images (e.g., of one or more lateral sides 102L) and top view images (e.g., of the top side 102T).

[0068] Once, and if desired, in substantial conformance with the controller 199, the processor 199P constructs the (one or more) composite images of the fully imaged stowed goods, as described, then the controller 199 calculates a variety of quantitative measurements by the Figure 7 process steps illustrated in. Referring to Figure 8 , examples of quantitative measurements include: "true box", "maximum box", "maximum bulge", "orientation angle", "distance from one side of the conveyor".

[0069] The "true box" measurement ( Figure 7 , box 710) includes the dimensions of the best-fit shape, which can be determined based on or obtained from the combined stowed goods image. For example, the shape employed in this fit is a box having length, width, and height. Alternatively, the shape employed can be a sphere having a center and a radius. A variety of other shapes can be employed in this fit, such as but not limited to cylinders, ovoids, cones, and the like. Figure 9 , 9A , 9B and 9C illustrate examples of the "true box" measurement (in Figure 9In the [description], it is shown by dashed lines on the processed images 900A and 900B, and the processed images 900A and 900B respectively represent elevation and plan combined images. This "true box" measurement is obtained from the composite images acquired / combined / constructed during the inspection of the packed goods 102, 200, 210 shown in Figure 1 and 2A and 2B. As can be seen in this example, when the "true box" dimensions are determined, any protrusions (such as the protrusions 220 in Figure 2A and 2B or protrusions not yet identified as box flaps as shown in Figure 9C ) and / or the protrusions 2400 seen by the vision system 150 are not so recognized. Here, the true box dimensions include the true box length RBL, the true box width RBW, and the true box height RBH. In this example, on the packed goods 200 illustrated in Figure 2A , the label LAB represents the packed goods 102, and can be partially disassembled and detected in the restricted image, and is analyzed as a part for optimal fit shape determination so as to be ignored in the occupied space evaluation. However, for example, opaque or translucent material packaging embodied in composite materials is included in the true box measurement to the extent that it conforms to the optimal fit shape.

[0070] The "outer box" measurement ( Figure 7 , frame 712) includes the dimensions of the smallest shape that encloses the complete product, and the dimensions of this smallest shape can be determined based on the combined product image or obtained from the combined product image (such as the protrusions 220 seen by the vision system, including distressed product parts, labels, and packaging). For example, the shape adopted in this fit is a box with length, width, and height, and the length, width, and height indicate the maximum rectangular occupied space of the packed goods 102 on the conveyors 110, 120. Alternatively, the shape adopted can be a sphere with a center and a radius. Various other shapes can be adopted in this fit, such as but not limited to cylinders, ovoids, cones, etc. Figure 9A and 9B , 9C and 10 illustrate examples of the "outer box" measurement (shown by dashed lines on the processed image), and this measurement is obtained from Figure 1 and 2AImages (1000A, 1000B) obtained / combined / constructed during the inspection period of the packed goods 102 shown in FIGS. 2A and 2B (see also, for example, packed goods 200, 210), which images correspondingly represent elevation / side and plan / top combined images. As can be seen in this example, any protrusions 220 and / or bulges 2400 imaged by the vision system 150 (including such grey image projection portions indicating translucent or opaque packaging) are considered and included when the "outer box" dimensions are determined. Here, the outer box dimensions include the outer box length OBL, the outer box width OBW, and the outer box height OBH. In this example, on the packed goods 102 (see, for example, the packed goods 200 in Figure 2A ) the partially detached label LAB ( Figure 2A ) dominates the determination of the occupied space of the packed goods 102.

[0071] The "maximum bulge" measurement ( Figure 7 , box 714) is the longest dimension obtained from the inspected packed goods 102. Figure 11 Illustrates the "maximum bulge" measurement, which is obtained from the images 1100A, 1100B obtained / combined / constructed during the inspection period of the packed goods 102 shown in FIGS. Figure 1 , 2A and 2B (see also, for example, packed goods 200, 210) (using the same as Figure 9 , 10Similar conventions. Using the determined product orientation, the "maximum bulge" is the maximum caliper measurement in width, in length, and in height. As will be described herein, the bulging packed goods 102 may affect the handling, storage, and palletization characteristics of the packed goods 102 within the logistics facility 190. For example, bulges on one or more sides of the packed goods 102 may cause unstable stacking of the packed goods, such as when palletized. Bulges on one or more sides of the packed goods 102 may also cause improper reorientation of the packed goods 102, such as on a case turner of a storage and retrieval system, where the case turner is configured to rapidly rotate or turn the packed goods 102 to reorient the packed goods 102. Bulges on one or more sides of the packed goods 102 may cause incorrect measurement of the packed goods 102 by the automated transport vehicle 190ATV of the logistics facility 190, which may further cause missed pickups, improper transfer of the packed goods 102 to the automated transport vehicle 190ATV, and misplacement of the packed goods. As will be further described below, the maximum bulge can also be measured separately from the maximum caliper measurements in width, in length, and in height to determine the size of the bulge relative to the adjacent edges of the packed goods 102 (see Figures 11A - 11C ), in order to determine whether improper handling, storage, and palletization characteristics exist in any given packed goods 102. In one or more aspects, with respect to the maximum bulge on the width axis and the maximum bulge on the length axis (see Figure 11B ), only the maximum bulge on the length axis (e.g., on one of the transverse sides 102L1, 102L2 of the case goods) can be tracked, and only the maximum bulge in the width direction (e.g., on one of the longitudinal sides 102F, 102R of the case goods 102) can be tracked. Here, the maximum bulge in the length direction is assumed for both transverse sides, and the maximum bulge in the width direction is assumed for both longitudinal sides 102F, 102R.

[0072] The product "orientation angle" is the angle of the main axis of the product relative to the travel direction TD of the packed goods 102 on the conveyors 110, 120. Figure 8 Best illustrates the non-zero product "orientation angle" determined when the box is used for optimal fit (see also FIG. 24, which illustrates the zero product orientation angle of the packed goods 102A and the non-zero product orientation angle of the packed goods 102B). For exemplary purposes, the "orientation angle" measurement can be the main axis when an ovoid shape is used in the fit.

[0073] Reference Figure 8The "distance from one side of the conveyor" is determined as the minimum distance obtained between the packed goods 102 and any of the predetermined conveyor sides (expressed based on the width of the light sheet, see Figure 6 ).

[0074] It should be understood that aspects of the disclosed embodiments are not limited to being implemented in the order illustrated Figure 3 and 7 in the steps illustrated therein. In one or more aspects, the determination of the measurement and the condition test are performed in parallel, for example as the conveyors 110, 120 are advanced and confirmed. The order of the steps illustrated in Figure 3 and 7 can illustrate the hierarchical structure of an encoded logic decision network.

[0075] Once a substantial number of the above measurements are determined, the image analysis computer program of the controller 199 will compare the measurements ( Figure 7 , block 718) with the nominal values and acceptance tolerances provided (in Figure 7 , block 716) to the packed goods inspection system 100. For example, a programmable logic controller (PLC) (not shown) can provide at least some nominal values and acceptance tolerances for a given box inspected by the inspection system. Depending on the user / operator's preference, a "true box", "outer box", or "maximum bulge" can be considered to accept or reject the packed goods 102.

[0076] According to one or more aspects of the disclosed embodiments, as can be seen from the example of the original image illustrated in Figure 4 , the recorded light intensity does not change within the acquired image. To establish a normalized baseline value of the intensity as a comparison basis or reference, the intensity values of a select number of non-black pixels (e.g., about 10 sample images) are considered. In one aspect, the intensity values of about 33% of the median value images (e.g., from the selected number of sample images) are considered to establish a normalized value of the pixel intensity. By doing so, signal noise, light interference, etc. are eliminated in order to reduce false packed goods detection or false measurement. The sample images provided for the basis of determining the normalized baseline value of the intensity can be updated, refreshed on a rolling basis, as previously described, to resolve environmental changes due to environmental variations, debris on the aforementioned EM sources, and / or vision system components, etc.

[0077] By using the above process, the vision system 150 can automatically compensate for debris, etc. present on the window panels of the camera systems 181, 184. When this occurs, the original constructed / combined image shows a narrow line of constant pixel intensity 1200D, as in Figure 12as shown in the stitched line 1200A in. When a narrow line of pixels is detected, a warning can be sent to the operator / user of the packed cargo inspection system 100 (such as through the user interface 198) to alert the need to clean the window. Here, due to the normalization of the above light intensity process, such debris can be gradually repositioned or removed from the combined composite image of the packed cargo 102 constructed by the image processing algorithm by the processor 199P of the controller 199 within several iterations (encoder step, stepper motor step, seconds, etc.), and thus minimize the impact on the operation of the packed cargo inspection system 100.

[0078] In one aspect, the profile detection system 180 sends its decision (accept or reject) ( Figure 7 , frames 720A and 720B) and various measurements taken to, for example, the user interface 198 for subsequent use by the user / operator of the packed cargo inspection system 100 ( Figure 7 , frame 722). For example, at least the conveyors 110, 120 can be operated in any suitable manner to retrieve or discard the rejected packed cargo, and / or the operating rod can be actuated to transfer the rejected packed cargo to any suitable "rejected product" conveyor. In other aspects, a large "orientation angle" can be reduced by actuating any suitable component of the packed cargo inspection system 100 (such as a guide rail or other product reorientation mechanism). In still other aspects, the conveyors 110, 120 can be reversed so that the rejected packed cargo 102 can be rescanned. In other aspects, the profile detection system 180 sends its decision (accept or reject) and one or more of the various product measurements taken (such as product size, orientation, etc.) to the flap detection system 170 for facilitating flap detection, as described herein. In one or more aspects, the user interface 198 receives one or more of the above information from the profile detection system 180 and information from the flap detection system 170 (as described herein).

[0079] Referring again to Figure 1 and 1A -1C and Figure 13A - 13F , the flap detection system 170 and the profile detection system 180 are configured to operate in parallel with each other and substantially simultaneously, where both are integrated into the packed cargo inspection system 100. The flap detection system 170 is configured to detect one or more of open flaps, protrusions, and depressions that may not otherwise be detected as protrusions or external protrusions 220 of the box by the profile detection system 180. The flap detection system 170 detects the flap by approximating the flap as a substantially consistent flat surface 1410 (see Figure 14A - 14D), wherein the flap has a length / size that is consistent with (e.g., corresponding to) the length / size of the corresponding product / carton 102 as determined by, for example, the profile detection system 180. A partial or small flap (which is only a small portion of the length of the flap) or the side of the packed goods to which the partial or small flap is attached may not be identified as an open flap and can be detected by the profile detection system 180 under the above "true box - outer box" criterion. As will be described herein, the flap detection system 170 is configured to detect flaps, protrusions, and / or depressions on any outer side (e.g., top, bottom, front (e.g., leading longitudinal side), rear (e.g., trailing longitudinal side), and lateral sides) of any given product / carton 102, including flaps attached to the lower side of the product / carton (e.g., the bottom side of the product sitting on conveyors 110, 120).

[0080] As described above, the imaging of the outer sides of the packed goods 102 by the flap detection system 170 is substantially simultaneous with the imaging of the outer sides of the packed goods 102 using the profile detection system 180. For example, the imaging of the outer sides using the flap detection system 170 is simultaneous with the box image data obtained from using the profile detection system 180 (see Figures 5 - 6)The recording of the dimensions of the packed goods (by the processor 199P) occurs substantially simultaneously, where the processor 199P resolves the imaged packed goods into corresponding stock keeping units or SKUs (e.g., box identifiers with known dimensions stored in a memory accessible by the processor 199P) and identifies any external protrusions 220 of the box as open flaps. Here, both the flap detection system 170 and the profile detection system 180 substantially simultaneously image the packed goods 102 passing through the packed goods inspection system 100, where the time taken for the packed goods to pass through the packed goods inspection system 100 is on the order of about 0.1 seconds to about 0.01 seconds. For example, in one or more aspects where the flap detection system 170 does not have laser illumination, the illumination of the packed goods by the profile detection system 180 can be coordinated with the imaging performed by the flap detection system 170 such that there is a slight offset between the illumination of the packed goods 102 by the profile detection system 180 and the imaging of the packed goods 102 by the flap detection system 170 to avoid an illumination interface when the packed goods 102 are imaged by the flap detection system 170; however, it should be noted that for the time frame in which the packed goods 102 pass through the packed goods inspection system 100 (e.g., on the order of about 0.1 seconds to about 0.01 seconds), the imaging of the packed goods 102 by both the flap detection system 170 and the profile detection system 180 is substantially simultaneous. In one or more aspects where the flap detection system 170 includes illumination (such as from lasers 171L - 173L), the illumination of the flap detection system 170 can be continuously pulsed (or periodically pulsed - e.g., turned on and off at a predetermined interval) substantially simultaneously with the illumination of the packed goods 102 by the profile detection system 180 such that the imaging of the packed goods 102 by both the flap detection system 170 and the profile detection system 180 is substantially simultaneous. It should be noted that in one or more aspects, one or more of the lasers 171L - 173L have a fixed or predetermined orientation such that the scanning / imaging of the packed goods 102 by the flap detection system 170 is affected by the movement of the packed goods along the conveyor(s) 110, 120; while in other aspects, one or more of the lasers 171L - 173L are movable relative to the conveyor(s) 110, 120 such that the scanning / imaging of the packed goods 102 by the flap detection system 170 is affected by the movement of one or more of the lasers 171L - 173L and is independent of (or decoupled from) the movement of the packed goods along the conveyor(s) 110, 120.

[0081] As described herein, the contour inspection system 180 analyzes the case inspection characteristics of the above-mentioned packed goods 102, wherein at least a part of the open flap detection, dent detection, and bulge detection is implemented by the flap detection system 170. Similarly, the flap detection system 170 analyzes at least a part of the open flap detection, dent detection, and bulge detection, wherein the case inspection characteristics are analyzed by the contour inspection system 180. As will be described below, the controller 199 / processor 199P is configured to confirm that (i.e., confirm from the image data obtained from the contour inspection system 180) the corresponding packed goods 102 has the expected case shape; the controller 199 / processor 199P determines the conformance of the corresponding packed goods 102 to the predetermined case form adaptation characteristics from other image data (i.e., from the flap detection system 170) for the handling, storage, and palletization of the packed goods 102 within the logistics facility 190. As will be described in more detail herein, the predetermined case form adaptation characteristics inform the assembly acceptance of the corresponding packed goods 102 within a predetermined assembly space or location of the logistics facility 190 (e.g., the storage space of the storage array 190SA or other holding positions, the payload compartment of the automated transport vehicle 190ATV, the pallet load building position in the pallet building formed within the logistics facility 190, etc.). As described herein, in one or more aspects, the predetermined case form adaptation characteristics are the inward bulges or dents of at least one side 102T, 102L, 102F, 102R of the case shape of the corresponding packed goods relative to the flat case side.

[0082] In one or more aspects, the packed goods contour inspection and the open flap detection (including dent detection and bulge detection) can be implemented independently of each other but generally simultaneously. For example, the contour inspection system 180 is not hindered by the open flap condition, dents, and / or bulges of the packed goods 102, and analyzes the case inspection characteristics (for the packed goods that meet the inspection criteria of the contour inspection system 180) independently of the occlusion of the open flap, dents, and / or bulges and the shielding of the outer side of the case from the sensors 171-173 of the flap detection system 170.

[0083] Although the flap detection system 170 can be initialized from the contour inspection system 180, which analyzes the case external protrusions 220 of the packed goods 102 that are acceptable / pass the contour inspection criteria Figure 2A and 2B)(i.e., bins that do not meet the case goods profile inspection criteria are rejected in any suitable manner, such as by diverting to a reject conveyor, removing by trained personnel, etc., as described herein), but the determination of open flaps, protrusions, and depressions is made by the flap detection system 170. Although protrusions on the side of the case goods 102 can be determined by both the flap detection system 170 and the profile detection system 180, the flap detection system 170 can provide more details about the protrusions for case handling (e.g., by the automated transport vehicle 190 ATV, palletizer 190 P, etc.) and case placement within the logistics facility 190( Figure 1 ). Suitable examples of storage and retrieval systems in which aspects of the disclosed embodiments can be deployed include, but are not limited to, those storage and retrieval systems described in the following patents: U.S. Patent No. 10,800,606, entitled "Material-Handling System Using Autonomous Transfer and Transport Vehicles," issued on October 13, 2020; U.S. Patent No. 10,556,743, entitled "Storage and Retrieval System," issued on February 11, 2020; U.S. Patent No. 10,633,184, entitled "Replenishment and Order Fulfillment System," issued on April 28, 2020; U.S. Patent No. 9,475,649, entitled "Pickface Builder for Storage and Retrieval Systems," issued on October 25, 2016; U.S. Patent No. 10,106,322, entitled "Bot Payload Alignment and Sensing," issued on February 23, 2018; U.S. Patent No. 10,703,585, entitled "Pallet Building System," issued on July 7, 2020; and U.S. Patent No. 10,781,060, entitled "Storage and Retrieval System Transport Vehicle," issued on September 22, 2020, the disclosures of which are incorporated herein by reference in their entirety.

[0084] As an example, regarding the detection of an open flap condition, for a packed cargo 102 that is acceptable to the profile inspection system 180, and using the identified external protrusions 220 of the box (i.e., determined from the profile inspection system 180), the controller 199 initializes the imaging of the packed cargo 102 using the sensors 171 - 173 of the flap detection system 170. When the flap detection system 170 determines the external protrusion 220 of the box to be an open flap, the controller 199 records the open flap condition in any suitable memory / database using the identification of the packed cargo 102 (e.g., the packed cargo identification number as shown in Tables 1 and 2 described herein) (note that the packed cargo 102 remains acceptable to the profile inspection system 180) for the disposal of the packed cargo 102 by any suitable packed cargo handling device (e.g., pallet stacker 190P, robotic arm, automated transport vehicle 190ATV, etc.). When the flap detection system 170 determines that the external protrusion 220 of the box is not an open flap, the controller 199 may not process the box image data 1400 from the sensors 171 - 173 of the flap detection system 170 (for exemplary image data, see Figure 14A - 1 4H). In one or more aspects, when the profile inspection system 180 does not detect an external protrusion 220 of the box, the controller 199 may initialize the flap detection system 170 for the sensors 171 - 173 to image the packed cargo 102, which is substantially simultaneous with the inspection of the packed cargo 102 by the profile inspection system 180, where the flap detection system 170 images the sides of the packed cargo 102 to detect external protrusions evident on each (or one or more) visible side of the packed cargo to verify the findings of the profile inspection system regarding the presence or absence of the external protrusion 220 of the box (note that the packed cargo remains acceptable to the profile inspection system 180).

[0085] As described herein, the flap detection system 170 is configured to image all (five) visible / non - seated sides of the packed cargo 102 (i.e., the five sides that are not seated on the conveyors 110, 120 and are visible to the sensors 171 - 173) (using at least one sensor 171 - 173). At least one sensor 171 - 173 is arranged to image each exposed box side 102T, 102L, 102R, 102F of each packed cargo 102 that is advanced through the packed cargo inspection system 100 using at least one conveyor 110, 120 to image the external protrusions 220 of the box that are evident on each imaged exposed box side 102T, 102L, 102R, 102F. In one or more aspects, the box image data 1400 captured by the sensors 171 - 173 of each packed cargo 102 (for exemplary image data, see Figure 14A - 1 4H) represents the corresponding external of the box 102E(Figure 1 ) each of the exposed case sides 102T, 102L, 102R, 102F. In one or more aspects, the case image data 1400 embodies the case exterior protrusions 220, where the case exterior protrusions 220 are apparent on at least one of the exposed case sides 102T, 102L, 102R, 102F, and the at least one exposed case side 102T, 102L, 102R, 102F is set in each exposed case side orientation of the stowed goods 102 (e.g., the case image data 1400 identifies the side on which an open flap is detected and / or the orientation of the open flap). In one or more aspects, the imaged exposed case sides 102T, 102L, 102R, 102F are set such that the open case flap 1300 resolved from the case exterior protrusions 220 apparent on the imaged exposed case sides 102T, 102L, 102R, 102F (see Figure 13A - 13F ) extends from the exposed case sides 102T, 102L, 102R, 102F and is adjacent to the conveyor seat surface CSS on which the stowed goods 102 are located (see Figure 13E ).

[0086] Figure 13A - 13F Illustrates an exemplary open flap configuration that the flap detection system 170 is configured to detect. Figure 13A Illustrates a lateral side view of the stowed goods 102, where the leading edge flap 1300TA attached to (e.g., hinged at) the edge of the top 102T is partially open at an angle α. Here, the angle α is illustrated as an acute angle, but can be any angle in the range from about 1° to about 270°. Figure 13B Is a lateral side view of the stowed goods 102, where the flap 1300TA that is attached to or otherwise hinged at the leading edge of the top 102T is open at an angle α, while the flap 1300TV that is attached to or otherwise hinged at the trailing edge of the top 102T is open at approximately 90° relative to the top 102T. Figure 13C Is a lateral side view of the stowed goods 102, where the flap 1300FA that is attached to or otherwise hinged at the leading edge of the top 102T is inclined at an angle β, while the flap 1300RH that is attached to or otherwise hinged at the trailing edge of the top 102T is inclined at an angle θ or an angle of approximately 180°. Here, the angle β is illustrated as a reflex angle, and the angle θ is illustrated as approximately 180°; however, in other aspects, the angles β, θ can both be in the range from about 1° to about 270°. Figure 13D Is a lateral side view of the stowed goods 102, where both the leading edge and trailing edge flaps 1300TA1, 1300TA2 are inclined relative to the top at respective angles α1, α2, where the respective angles can be in the range from 1° to about 270°.Figure 13E is a lateral side view of the stowed cargo 102, where the flap 1300BA hinged at the leading edge of the bottom 102B of the stowed cargo 102 is opened at an angle β2 relative to the bottom 102B, and the flap 1300BR hinged at the trailing edge of the bottom 102B of the stowed cargo 102 is opened at an angle θ2 of approximately 180° relative to the bottom. Here, the angle β2 is illustrated as a reflex angle, and the angle θ2 is illustrated as approximately 180°; however, in other aspects, the angles β, θ can both be in the range from approximately 1° to approximately 270°. Figure 13F is a plan view of the top 102T of the stowed cargo 102, where the flap 1300VR on the lateral side edge of the rear or trailing side 102R of the stowed cargo 102 is opened at an angle α3 relative to the rear side 102R. Here, the angle α3 is illustrated as an acute angle, but can be any angle in the range from approximately 1° to approximately 270°. As described above, FIGS. 130A - 130F are non - limiting illustrative examples of the flap orientations that the flap detection system 170 is configured to detect. As can be appreciated, the product 102 illustrated in Figure 13A - 13D can have any orientation on the conveyors 120, 110 such that the hinged side of the flap extends in a generally lateral direction relative to the conveyors 120, 110 or in a generally longitudinal direction (i.e., along the direction of travel of the conveyor) relative to the orientation of the conveyors 120, 110, or has any other orientation therebetween.

[0087] Still referring to Figure 1 And also referring to Figure 13A - 13F and 14A - 14H, and as described above, the flap detection system 170 includes at least one sensor / imaging device 171 - 173, which is arranged to capture product / box image data 1400 of each stowed cargo or product 102 propelled by the conveyors 110, 120 by the at least one sensor / imaging device 171 - 173 (for exemplary image data, see Figure 14A - 14H). At least one sensor / imaging device 171-173 captures image data 1400 at any suitable resolution to enable open flap determination as described herein. For illustrative purposes only, the image resolution provided by the at least one sensor / imaging device is approximately 3 mm (about 0.1 in) in the X direction (e.g., generally parallel to the direction of product flow along conveyors 110, 120), approximately 1.5 mm (about 0.05 in) in the Y direction (e.g., in the plane defined by the product support surface of conveyors 110, 120 and generally perpendicular to the direction of product flow along conveyors 110, 120), and approximately 1.5 mm (about 0.05 in) in the Z direction (e.g., generally perpendicular to the product support surface CSS of conveyors 110, 120). In other aspects, the resolution in one or more of the X, Y, Z directions may be greater than or less than the above resolution.

[0088] As described above, the controller 199 (including its processor 199P) is coupled to conveyors 110, 120 and communicatively coupled to at least one sensor / imaging device 171-173 to receive bin image data 1400 from the at least one sensor / imaging device 171-173. Here, the triggering of the at least one sensor / imaging device 171-173 is implemented in the manner described above, such as through the profile detection system 180, or in a manner generally similar to that described above with respect to the profile detection system 180. In one or more aspects, the flap detection system 170 performs one or more image acquisitions into an image buffer (such as the image buffer of the controller 199 processor 199P), where the image acquisition is triggered by a conveyor encoder or alternatively by a stepper motor drive circuit that advances at least one of the conveyors 110, 120. In other aspects, the image acquisition may be implemented in any suitable manner (such as using a motion sensor, etc.).

[0089] As will be described herein, the controller 199 (e.g., by any suitable non-transitory computer program code) is configured to characterize the bin exterior protrusions 220 of the stuffed goods 102 (see Figure 2A and 2B ) from the bin image data 1400 as flaps 1300TA, 1300TA1, 1300TA2, 1300TV, 1300FA, 1300RH, 1300BA, 1300BR, 1300VR (commonly referred to as flaps or bin flaps 1300) in an open condition (see, for example, Figure 13A - 13F)(e.g., an open box flap). The controller 199 (via the processor 199P) is configured to parse the box image data 1400 and determine that the box exterior protrusion 220 is a consistent flat surface 1410. The processor 199P is programmed with a parameter array 199A of physical property parameters ( Figure 1 — also referred to herein as the parameter array 199A), the physical property parameters describing the box flap consistency attributes that determine a consistent flat surface 1410 defining the condition of an open box flap. The processor 199P is configured to generate (e.g., using any suitable computer program code implementing its generation) a physical property array 199C from the box image data 1400 for each determined consistent flat surface 1410, and apply the parameter array 199A to the physical property array 199C to parse the consistent flat surface 1410 as an open box flap, such as illustrated in Figure 13A - 13F and 14A - 14H. Here, the physical property array 199C describes the consistent flat surface as a box flap and determines that the box flap is in an open flap condition based on the parameter array 199A of physical property parameters.

[0090] The processor 199P is configured to (in addition to or instead of parsing the open box flap condition) parse the box image data 1400 and determine that at least one box top 102T or at least one box side 102L, 102R, 102F has an inward variation (i.e., a depression). The processor 199P is programmed with a parameter array 199A of physical property parameters, the physical property parameters describing the inward variation attributes that determine an inward variation defining a depression condition. The processor 199P is configured to generate a physical property array 199C from the box image data 1400 for each determined inward variation, and apply the parameter array 199A to the physical property array 199C to parse the inward variation as a depression condition. Although the parameter array 199A and the physical property array 199C are described as including both open flap and depression characteristics, in other aspects, there may be separate parameter and physical property arrays for each of the open flap and depression characteristics.

[0091] The parameter array 199A of physical property parameters (also referred to herein as the parameter array 199A — see Figure 1)Is programmed into the controller 199 and is accessible by the processor 199P. The parameter array 199A of physical property parameters describes one or more case flap consistency attributes or characteristics of a consistent plane, and the case flap consistency attributes or characteristics determine and describe the consistency of a plane (e.g., the consistent flat surface 1410) with respect to, for example, the dimensions of the packed goods (the length, width, and height of the corresponding packed goods received by the controller 199 from the profile detection system 180). The consistent flat surface 1410 defines an open case flap condition and includes any appropriate physical properties for a given packed goods / product configuration and / or flap configuration. The consistent plane or consistent flat surface 1410 depends on the physical properties and is resolved by any appropriate image processing of the controller 199, where the controller 199 determines (e.g., from one or more of the profile detection system 180 and the flap detection system 170) the presence of case external protrusions 220( Figure 2A and 2B ), and then determines whether the case external protrusions are the consistent plane based on the physical properties of the consistent plane. For example, the processing of the image data from the flap detection system 170 determines whether the consistent plane converges to define an edge with at least one of the case sides (e.g., the top, lateral sides, and longitudinal sides). When it is determined that there is an edge with at least one of the case sides and the physical properties or parameters in the physical property array 199C are satisfied, the controller 199 determines that an open flap exists and records the open flap with the identification of the corresponding packed goods 102 for further processing of the corresponding packed goods 102.

[0092] In the examples provided herein, the physical properties or parameters in the physical property array 199C include five parameters (as described below), but it should be understood that in other aspects, there may be more or fewer than five parameters employed for the determination of the open flap condition. These parameters are applied to each of the visible sides of the packed goods 102 (e.g., the top 102T, longitudinal sides 102, 102R, and lateral side 102L) for the determination of the open flap condition on each side, where the recording of the open flap condition can be not only with respect to the identification of the corresponding packed goods, but also with respect to the side of the corresponding packed goods on which the open flap exists. Knowing on which side the open flap exists can facilitate the further processing of the corresponding packed goods by automated equipment or the determination of the rejection of the packed goods.

[0093] Note that the physical properties in the parameter array 199A and the physical property array 199C are characteristics of the packed goods 102 that are different from those of the packed goods 102 imaged by the profile detection system 180 (as described above). For example, also refer to Figures 15 - 20, both the parameter array 199A and the physical property array 199C include, but are not limited to, five threshold parameters (again, more or fewer than five may be employed), which are:

[0094] - The minimum opening angle of the flap (e.g., the minimum angle α from the horizontal edge of the packed goods 102 MH and the minimum angle α from the vertical edge of the packed goods 102 Mv - See Figure 15 and 16 ),

[0095] - The minimum flap depth MFD relative to the base of the flap (e.g., the distance from the hinged side HS or base of the flap to the opposite free side FS of the flap - see Figure 18 ), in some aspects, this parameter can be expressed as a ratio,

[0096] - The ratio of the minimum flap length MFL to the product box length PBL (e.g., MFL / PBL) (see Figure 17 ),

[0097] - The minimum product box length (or width) L increased by the flap (e.g., L is the total length MPBLF of the product with the open flap 1300 minus the product box length PBL - see Figure 19 ), note that the minimum product box length (or width) is a function of the minimum angle α from the horizontal edge of the packed goods 102 MH and / or the minimum angle α from the vertical edge of the packed goods 102 Mv and,

[0098] - The minimum product box height BH increased by the flap (e.g., BH is the total height MPBHF of the product with the open flap 1300 minus the product box height PBH - see Figure 20 ), note that the minimum product box height is a function of the minimum angle α from the horizontal edge of the packed goods 102 MH and / or the minimum angle α from the vertical edge of the packed goods 102 MV of the function.

[0099] The detection system 170 is configured to reject the packed goods 102 when one or more of these parameters / thresholds are exceeded. In one or more aspects, the flap detection system 170 is configured to reject the packed goods 102 when each or all of the following are exceeded: the minimum opening angle α of the flap MH , α MV; the minimum flap depth MFD; the ratio of the minimum flap length MFL to the product box length PBL; and the minimum product box length (or width) MPBLF increased by the flap (or the minimum product box height MPBHF increased by the flap, depending on whether the flap is located on the vertical or horizontal side of the product). In still other aspects, the flap detection system 170 is configured to reject the stuffed cargo 102 when each or all of the following are exceeded: the minimum opening angle α of the flap MH 、α MV ; the minimum flap depth MFD; the ratio of the minimum flap length MFL to the product box length PBL; and the minimum product box length (or width) MPBLF increased by the flap (MPBLF is conditional on the minimum opening angle α MH 、α MV ), and the minimum product box height MPBHF increased by the flap (MPBHF is conditional on the minimum opening angle α MH 、α MV ). The rejected stuffed cargo 102 can be routed away from the conveyor, and / or the operator can be informed of the rejection through the user interface 198, in a manner generally similar to that described above for the profile detection system 180.

[0100] For illustrative purposes only, the minimum opening angle α of the flap MH 、α MV is 15°, the minimum flap depth MFD is approximately 20 mm (approximately 0.7 in), the ratio of the minimum flap length MFL to the product box length PBL is approximately 50%, the minimum product box length (or width) MPBLF increased by the flap is approximately 20 mm (approximately 0.7 in), and the minimum product box height MPBHF increased by the flap is approximately 20 mm (approximately 0.7 in). In other aspects, the minimum opening angle α of the flap MH 、α MV 、the minimum flap depth MFD, the ratio of the minimum flap length MFL to the product box length PBL, the minimum product box length (or width) MPBLF increased by the flap, and the minimum value of the minimum product box height MPBHF increased by the flap can be greater than or less than the above values.

[0101] As described herein, the flap detection system 170 and the profile detection system 180 operate in parallel, with at least some information (bin image data) shared between the systems. For example, to determine if at least some of the above parameters are exceeded, the profile detection system 180 sends information about the physical characteristics of any given bin (e.g., length, width, height, orientation on conveyors 110, 120, and in some aspects, the presence of bin exterior protrusions 220) to the flap detection system 170, such that the flap detection system 170 determines if the parameter / threshold is exceeded. For example, referring to Figure 1 and 21 , in operation, the flow of products 102P1, 102P2, 102P3 moves along conveyors 110, 120 through the profile detection system 180 and the flap detection system 170. As each packed product 102P1, 102P2, 102P3 passes through the profile detection system 180, the profile detection system 180 detects the product characteristics of each of these packed products 102P1, 102P2, 102P3 (e.g., length, width, height, protrusions, orientation, etc. on the conveyor, as described herein), and sends at least some of the detected information to the flap detection system 170. For example, the flap detection system 170 may employ the length, width, height, and orientation of each respective packed product 102P1, 102P2, 102P3 in combination with the image data 1400 captured by the flap detection system 170 to determine the presence of an open flap. The flap detection system 170 may also employ any detection of protrusions by the profile detection system 180 to identify regions of interest for the respective packed products 102P1, 102P2, 102P3 where an open flap may be present.

[0102] Also referring to Figure 14A - 1 4H, in one or more aspects, the physical characteristics obtained by the flap detection system 170 from the profile detection system 180 are compared with the image data captured by the flap detection system 170 to, for example, confirm or verify the position of each product in the product flow (e.g., the products pass through the flap detection system 170 in the same order as they pass through the profile detection system 180), and to determine if the products that have passed through the profile detection system 180 are suitable for storage, handling, and palletizing in the logistics facility 190 ( Figure 1 ). The physical characteristics obtained by the profile detection system 180 may also be employed by the flap detection system 170 to verify at least some of the physical characteristics of products 102P1, 102P2, 102P3, as determined by the flap detection system 170 from the image data 1400.

[0103] Referring to Figure 14A, an example of the image data 1400 captured by the flap detection system 170 is illustrated. For explanatory purposes, the image data 1400 illustrated in Figure 14A is a planar or top view of the packed goods 102P1. Here, the image data is point cloud data, but can be any suitable image data for implementing image analysis for detecting packed goods / product features. In this example, the flap detection system 170 (through any suitable image processing algorithm / program) determines that the protrusions or external protrusions 1450, 1451 of the box (which may have been identified as external protrusions of the box by the contour detection system 180, but not identified as open flaps) are a consistent flat surface 1410 and identifies these external protrusions 1450, 1451 of the box as open flaps 1300A, 1300B. The flap detection system 170 constructs an array 199C of the physical characteristics of the packed goods 102P1 based on the image data 1400 (see Figure 1 , Table 1, Table 2 below), where the array 199C of physical characteristics includes, for example, the flap angle α vD (from the vertical side of the product) and the flap length L D (from the vertical side). The controller 199 compares the data in the array 199C of physical characteristics with the corresponding data in the array 199A of parameters to determine whether any thresholds / parameters in the array 199A of parameters are exceeded. For example, in Figure 14A , the flap angle α vD may be greater than the minimum angle α Mv , while the length L D of the flaps 1300A, 1300B is less than the length L. Here, based on at least these two parameters when compared with the corresponding values of the array 199A of parameters (and the insight that the packed goods are rejected if more than one of the following is exceeded: the minimum opening angle α MH , α MV ; the minimum flap depth MFD; the ratio of the minimum flap length MFL to the product box length PBL; the minimum product box length (or width) L increased by the flap; and the minimum product box height BH increased by the flap), the packed goods 102P1 are acceptable and not rejected (e.g., depending on whether other parameters are exceeded, and / or how many parameters and which parameters are considered in the rejection determination).

[0104] Figure 14B is another exemplary illustration of the image data 1400 captured by the flap detection system 170. For explanatory purposes, in Figure 14BThe image data 1400 illustrated therein is a lateral side view of the packed goods 102P2. Here, the image data is point cloud data, but can be any suitable image data for implementing image analysis for detecting product features. In this example, the flap detection system 170 (by any suitable image processing algorithm / program) determines that the protrusion or external protrusion 1452 of the box (which may have been identified as the external protrusion 220 of the box by the contour detection system 180 but not identified as an open flap) is a consistent flat surface 1410 and identifies the external protrusion 1452 of the box as an open flap 1300 (e.g., an open flap hinged to the bottom side 102B of the packed goods 102P2). The flap detection system 170 constructs an array 199C of physical characteristics of the packed goods 102P2 based on the image data 1400( Figure 1 ), where the array 199C of physical characteristics includes at least the flap length L D and the flap angle α vD . For example, in Figure 14B , the flap angle α vD may be greater than the minimum angle α Mv , and the length L of the flap 1300 D may be the length L. Here, based on at least these two parameters when compared with the corresponding values of the parameter array 199A (and the insight that the packed goods are rejected if more than one of the following are exceeded: the minimum opening angle α MH 、α MV ; the minimum flap depth MFD; the ratio of the minimum flap length MFL to the product box length PBL; the minimum product box length (or width) L increased by the flap; and the minimum product box height BH increased by the flap), the packed goods 102P2 can be rejected (e.g., depending on whether other parameters are exceeded, and / or how many parameters and which parameters are considered in the rejection determination).

[0105] Figure 14C is another exemplary illustration of the image data 1400 captured by the flap detection system 170. For explanatory purposes, in Figure 14BThe image data 1400 illustrated therein is a front (or rear / back) side view of the packed goods 102P3. Here, the image data is point cloud data, but can be any suitable image data for implementing image analysis for detecting features of the packed goods / products. In this example, the flap detection system 170 (by any suitable image processing algorithm / program) determines that the protrusions or external protrusions 1453, 1454 of the box (which may have been identified as external protrusions of the box by the contour detection system 180 but not identified as open flaps) are a consistent flat surface 1410 and identifies the external protrusions 1453, 1454 of the box as open flaps 1300A, 1300B (e.g., open flaps hinged to the top side 102T of the packed goods 102P3). The flap detection system 170 constructs an array 199C of physical characteristics of the packed goods 102P3 based on the image data 1400( Figure 1 ), where the array 199C of physical characteristics includes at least the flap height BH D and the flap angle α HD . For example, in Figure 14C , the flap angle α HD of the flap 1300A may be less than the minimum angle α MH , the flap angle α HD of the flap 1300B may be greater than the minimum angle α MH , the height of the flap 1300A is less than the height BH, and the height BH D of the flap 1300B is greater than the height BH. For example, here, based on at least the parameters of the flap 1300B when compared with the corresponding values of the parameter array 199A (and the insight that the packed goods are rejected if more than one of the following is exceeded: the minimum opening angle α MH , α MV ; the minimum flap depth MFD; the ratio of the minimum flap length MFL to the product box length PBL; the minimum product box length (or width) L increased by the flap; and the minimum product box height BH increased by the flap), the packed goods 102P2 can be rejected (e.g., depending on whether other parameters are exceeded, and / or how many parameters and which parameters are considered in the rejection determination).

[0106] Figures 23A - 23C are other exemplary illustrations of the image data 1400 captured by the flap detection system 170. For explanatory purposes, in Figure 23AThe image data 1400 illustrated therein is a front (or rear / back) perspective view of the stowed cargo 102, where a box-side indentation 2300 is present, for example, on the top of the stowed cargo 102 (note that the box-side indentation can be present on any visible side of the stowed cargo 102 for detection by the flap detection system 170). Here, the image data 1400 is photographic image data of the stowed cargo 102, but can be any suitable image data that enables image analysis for detecting stowed cargo / product features. Figure 23B illustrates Figure 23A the image data 1400 of the stowed cargo 102 as point cloud data.

[0107] In this example, the flap detection system 170 (by any suitable image processing algorithm) determines the presence of the box-side indentation 2300 by analyzing one or more sides of the stowed cargo 102, and if the box-side indentation 2300 is present, the flap detection system 170 determines the depth of the indentation 2300. As an example, the flap detection system 170 (e.g., based on a three-dimensional analysis of the stowed cargo 102) determines the presence of the box-side indentation 2300 by determining that one or more box sides do not describe a consistent flat surface within a predetermined flat surface threshold criterion (i.e., there is no consistent flat surface on one or more sides) (e.g., in a manner substantially opposite to that described above for the box exterior protrusion 220). For example, the absence of a consistent flat surface (or the presence of a non-uniform surface) on one side of the stowed cargo 102 can be determined by detecting one or more apertures 2310 that can be formed by, for example, box flaps 1300. When the box-side indentation 2300 is on a side of the stowed cargo 102 without flaps (or with flaps but the flaps are not separated to form apertures 2310 therebetween), the absence of a consistent flat surface can be determined by the flap detection system 170 by determining the presence of one or more of a recess 2340, a wrinkle 2320, and an aperture (perforation) 2330 on the side of the stowed cargo 102 (e.g., based on a three-dimensional analysis of the stowed cargo 102). The box-side indentation 2300 can be formed in any suitable region of the side of the stowed cargo 102. For example, the box-side indentation can be generally in the middle of the side (see, e.g., the recess 2340, the aperture 2330, and the box-side indentation 2300), at the edge of the side (see, e.g., the wrinkle 2320 and the box-side indentation 2300), and / or extend across the side to transition from the edge to the middle of the side (or beyond the side) (see, e.g., the wrinkle 2320 and the box-side indentation 2300).

[0108] For illustrative purposes only, if the lengthwise dimension (e.g., with respect to the length, width, and / or height of the stowed cargo), the widthwise dimension (e.g., with respect to the length, width, and / or height of the stowed cargo), or the diameter of the small hole 2310 (e.g., formed by the flap 1300) is greater than about 2 inches, then a sidewall indentation of the container is determined (in other respects, the criterion for determining a sidewall indentation of the container can be more or less than about 2 inches). Similar appropriate criteria are applied to the determination of the sidewall indentation 2300 based on the recess 2340, the wrinkle 2320, and the small hole (perforation) 2330.

[0109] When the sidewall indentation 2300 is present, the flap detection system 170 determines the depth 2399 of the non-uniform surface (e.g., indentation, recess, wrinkle, etc.), where the depth 2399 is measured from, for example, the edge 2323 of the stowed cargo formed by the side of the stowed cargo on which the non-uniform surface is present and the adjacent side of the stowed cargo (here, the depth 2399 is measured from the edge formed by the top 102T of the stowed cargo and one or more vertical sides (e.g., the lateral side 102L and / or the longitudinal sides 102F, 102R) of the stowed cargo - see also Figure 11A ). In other respects, the depth 2399 can be measured from any other appropriate reference point of the stowed cargo, such as the bottom or the opposite side with respect to the side on which the non-uniform surface is present.

[0110] Here, if the depth 2399 of the non-uniform surface is greater than a predetermined threshold (such as, for example, about 1 inch (about 25 mm)), the stowed goods 102 are classified as not suitable (i.e., rejected due to non-compliance with the corresponding predetermined case form fit characteristics) for case handling, storage, and palletizing within the logistics facility 190 and are removed from the automated handling within the logistics facility 190 in the manner described above. In addition to or instead of the depth criterion, the unsuitability of the stowed goods for case handling, storage, and palletizing within the logistics facility 190 can be determined by the side on which there is a non-uniform surface and / or the location (e.g., area of the side) of the non-uniform surface on that side of the stowed goods (and / or other suitable criteria that affect case stability when stacking or automatically transporting / handling the stowed goods). As an example, the vertical sides of the stowed goods 102 may have more stringent unsuitability criteria (e.g., reduced allowances / tolerances for depressions) than the horizontal sides of the stowed goods 102 because the vertical sides act as higher load-bearing members than the horizontal sides when the stowed goods are stacked for palletizing. Regarding the location (e.g., area of the side) of the non-uniform surface (such as, for example, depressions, recesses, wrinkles, small holes, etc.) on the side of the stowed goods, non-uniform surfaces located at the edges of the stowed goods 102 may be held to more stringent unsuitability criteria (e.g., reduced allowances / tolerances for depressions) compared to non-uniform surfaces in the middle / center of the side. For example, non-uniform surfaces located at the edges of the stowed goods 102 may provide less stability when stacking the stowed goods for palletizing or may create features on the stowed goods 102 that trigger a "catch" or "snag" that would otherwise interfere with case handling.

[0111] Figure 24Ais another exemplary illustration of the image data 1400 captured by the flap detection system 170. For explanatory purposes, the image data 140 illustrated in FIG. 24 is a front (or rear / back) perspective view of the packed goods 102, where a box bulge 2400 is present, for example, on the top of the packed goods 102 (note that the bulge 2400 can be present on any visible side of the packed goods 102 for detection by the flap detection system 170). Here, the image data 1400 is photographic image data of the packed goods 102, but can be any other suitable image data that enables image analysis for detecting packed goods / product features. In a manner similar to that described above, a three-dimensional analysis of the packed goods 102 by the flap detection system 170 determines that, for example, the top side 102T of the packed goods 102 is a non-uniform surface; while the top side 102T is used as an example, non-uniform surfaces can be present on and determined to be on any one or more of the top, lateral, and longitudinal sides 102T, 102L, 102R, 102F of the packed goods 102. In one or more aspects, a bulge can be detected on the bottom surface 102B of the packed goods 102, such as based on the determination of the space 2450 formed by the bulge between the bottom surface 102B of the packed goods 102 and the conveyors 110, 120 (e.g., a determination made by the flap detection system 170 and / or the profile detection system 180) (see Figure 24B ).

[0112] Based on a three-dimensional analysis of the packed goods 102, the flap detection system 170 determines the height 2499 of the bulge 2400 formed by the non-uniform surface. The height 2499 is measured, for example, from the edge 2424 of the packed goods formed by the side of the packed goods on which the non-uniform surface is present and the adjacent side of the packed goods (here, the height 2499 is measured from the edge formed by the top 102T of the packed goods and one or more vertical sides (e.g., the lateral side 102L and / or the longitudinal sides 102F, 102R)) (also see Figures 11A - 11C ). In other aspects, the height 2499 can be measured from any other suitable reference point or datum of the packed goods, such as the bottom or the opposite side with respect to the side on which the non-uniform surface is present. In other aspects, instead of or in addition to the flap detection system 170's determination of the bulge 2400, the bulge 2400 can be determined by the profile detection system 180, and the image data from the profile detection system 180 can be used by the flap detection system 170 in a manner similar to that described above to determine the bulge dimensions (e.g., the three-dimensional profile of the bulge) and the conformity of the corresponding packed goods 102 to the predetermined form-fit characteristics, to generally ensure the proper handling, storage, and palletization of the corresponding packed goods 102 within the logistics facility 190.

[0113] Here, if the height 2499 of the non-uniform surface is greater than a predetermined threshold (e.g., a bulge such as about 1 inch (about 25 mm); or more or less than about 1 inch (about 25 mm) in other aspects), the stuffed goods 102 are classified as not suitable (i.e., rejected due to non-compliance with the corresponding predetermined box form adaptation characteristics) for box handling, storage, and palletization within the logistics facility 190, and are removed from the automated handling within the logistics facility 190 in the manner described herein. In addition to or in lieu of the height criterion, the unsuitability of the stuffed goods for box handling, storage, and palletization within the logistics facility 190 is determined by the side on which the non-uniform surface exists and / or the position (e.g., the area of the side) of the non-uniform surface on that side of the stuffed goods (and / or other appropriate criteria that affect the box stability when stacking or automatically transporting / handling the stuffed goods). As an example, the vertical side of the stuffed goods 102 may have a more stringent criterion than the horizontal side of the stuffed goods 102 because when the stuffed goods 102 are stacked for palletization, the vertical side acts as a higher load-bearing member than the horizontal side. Regarding the position of the (one or more) bulges, a non-uniform (bulging) surface at a corner, diagonal corner, or middle / center of the stuffed goods 102 may provide less stability when stacking the stuffed goods for palletization, or may create features that cause "hooks" or "sharp corners" on the stuffed goods that would otherwise interfere with box handling, and may be held to a more stringent unsuitability criterion compared to a bulging surface along substantially the entire edge.

[0114] In addition to or in lieu of the determination of one or more of the above box goods characteristics (e.g., dents, open flaps, true boxes, maximum boxes, maximum bulges (as determined by one or more of the box inspection system 180 and the flap detection system 170), external boxes, length of the protrusion / open flap, orientation angle, distance from one side of the conveyor, etc.), the box inspection system 180 and / or the flap detection system 170 (using information from the box inspection system 180) are configured to determine one or more of the following: multiple box detections ( Figure 29 ), verification of vertical items inside the stuffed goods ( Figure 26 ), maximum narrowing at the top and / or bottom of the stuffed goods ( Figure 11C , 25 and 27), and the support surface of the tapered box goods ( Figure 25 and 26 ) for determining the compliance of the corresponding stuffed goods with the predetermined box form adaptation characteristics.

[0115] Reference Figure 29, an example planar / top image of a plurality of packed goods 102A, 102B traveling along conveyors 110, 120 is provided. The image illustrated in Figure 29 can be provided by one or more of the case inspection system 180 and the flap detection system 170. The controller 199 is configured to: distinguish each of the plurality of packed goods 102A, 102B using the image data obtained from the case inspection system 180 and / or the flap detection system 170, and determine (in the manner described herein) the packed goods characteristics described herein for each of the packed goods 102A, 102B.

[0116] Referring to Figure 25 , an exemplary image (such as an image obtained by the flap detection system 170 and / or the case inspection system 180) is provided, and the top taper TP3 of the packed goods 102 is illustrated. Note that Figure 25 the exemplary image shown in is a side view (lengthwise axis) of the packed goods 102 with a substantially zero orientation angle. In other aspects where the orientation angle is substantially 90 degrees, a similar side view (widthwise axis) image is obtained. When the orientation angle of the packed goods 102 on the conveyors 110, 120 does not provide an elevation (e.g., a substantially straight side) view, but rather an isometric view of the packed goods 120, three-dimensional image data from the flap detection system 170 (which is used in some aspects in combination with data from the case inspection system 180) can be employed by the controller 199 to determine the top taper TP3 of the packed goods along one or more of the lengthwise and widthwise axes. The top taper TP3 is measured from a plane defined, for example, by the bottom side 102B (i.e., the seating surface) of the packed goods 102, which seats against the surface of the conveyors 110, 120 (or otherwise seats against a support surface of a storage / holding position, or another packed good in a stack of packed goods). When the top taper TP3 exceeds a predetermined threshold (e.g., the predetermined threshold is based on the stability of other packed goods stacked on top of the packed goods 102, such as, for example, about 1 inch (about 25 mm) - in other aspects, the predetermined threshold can be more or less than about 1 inch (about 25 mm)), the packed goods are rejected in the manner described herein.

[0117] The controller 199 is configured to present the top taper TP3 information to the user / operator in any suitable manner, such as via the user interface 198. For example, the controller indicates the amount of taper (along one or more of the length and width axes), the axis along which the taper is determined (e.g., the length or width direction), and the orientation angle of the case goods. When the determination of the top taper TP3 is not available, the controller 199 provides an indication of the top taper unavailability (e.g., via the user interface 198) to the user. The top taper can be employed at least when determining the pallet building plan using the controller 199.

[0118] Still referring to Figure 25 , an exemplary image (which is obtained from one or more of the case inspection system 180 and the flap detection system 170) illustrates the top narrowing of the case goods 102 in the form of a tray 2520 containing round bottles. The exemplary image is a substantially two-dimensional image of the case goods 102; however, in other aspects, a three-dimensional image can be provided. Here, the top narrowing indicates a reduction in the value (i.e., surface area) of the top 102T of the case goods 102 relative to the bottom 102B. Here, the leading longitudinal side 102F of the case goods 102 includes a taper having an angle TP1, as measured from, for example, a plane defined by the non-tapered portion of the longitudinal side 102F. The trailing longitudinal side 102R of the case goods 102 includes a taper having an angle TP2, as measured from, for example, a plane defined by the non-tapered portion of the longitudinal side 102R. These tapers TP1, TP2 are translated into narrowing values DP1, DP2, which inform the reduced surface area of the top 102T of the case goods relative to the bottom 102B.

[0119] The narrowing values DP1, DP2 may affect the ability of the case goods to be palletized such that the reduced surface area (i.e., support surface) of the top 102T caused by the tapers TP1, TP2 cannot stably support other case goods 102 stacked thereon. When the case goods 102 are substantially symmetric, such as for Figure 25For the case of the packed goods containing round bottles, the larger of the narrowing values DP1, DP2 is assumed to be used for both the lengthwise and widthwise axes of the packed goods; while in other aspects, the tapers TP1, TP2 and the resulting narrowing values DP1, DP2 can be determined (such as being determined from: three-dimensional image data from the flap detection system 170, or a combination of image data from both the flap detection system 170 and the case inspection system 180) for each side 102F, 102R, 102L1, 102L2 of the packed goods 102. In other aspects, such as where the packed goods 102 include asymmetric contents (e.g., a mayonnaise bottle having one flat side and one side including a taper of the bottle neck), the narrowing values DP1, DP2 are provided for only one of the lengthwise and widthwise axes, but the larger of the narrowing values DP1, DP2 is assumed to be used for both the lengthwise and widthwise axes. In the case of the bottle, the maximum narrowing value can be substantially the same as the expected distance EDP between the edge 2510 defined by the tray / package 2520 holding the bottle and the outer periphery of the bottle cap 2530 (see Figure 25A ); while in other aspects, the maximum narrowing value can be greater than or less than the expected distance EDP.

[0120] Reference Figure 27, an exemplary image (which is obtained from one or more of the case inspection system 180 and the flap detection system 170) illustrates the narrowing of the top of the packed goods 102 in the form of a box. The exemplary image is a generally two-dimensional image of the packed goods 102; however, in other aspects, a three-dimensional image may be provided. In the illustrated example, the narrowing values DP1, DP1 inform of a tilted / deformed box; however, in other aspects, the narrowing values DP1, DP2 may indicate a reduction in the value (i.e., surface area) of the top 102T of the packed goods 102 relative to the bottom 102B, such as where the top 102T of the packed goods is wrinkled (see FIG. 23) or otherwise deformed. Here, the top edge TEF of the packed goods 102 on the leading lateral side 102L1 is offset by a narrowing value DP1 relative to the bottom edge BEF of the packed goods 102 on the leading lateral side 102L1. Here, the top edge TER of the packed goods 102 on the trailing lateral side 102L2 is offset in the same direction as the top edge TEF by a narrowing value DP2 relative to the bottom edge BER of the packed goods on the trailing lateral side 102L2. The narrowing of the top edges TEF, TER in the same direction informs of the tilt of the packed goods 102, which may affect the stability of the packed goods 102, such as when being palletized, because the tilt may cause a repositioning of the center of gravity of the packed goods from CG1 to CG2. In one or more aspects, the larger of the narrowing values DPI, DP2 that inform of the tilt of the packed goods 102 is assumed for both the width direction and the length direction axes. In the case of the packed goods 102 in the form of a box, the maximum narrowing value may be about 1 inch (about 25 mm); in other aspects, the maximum narrowing value may be greater than or less than about 1 inch (about 25 mm).

[0121] In the above example, if the narrowing values DP1, DP2 exceed a predetermined maximum narrowing value, the packed goods 102 are rejected in the manner described herein. In a manner similar to the above, the maximum narrowing value may be based on the stability of the packed goods when being palletized. In one or more aspects, the determined narrowing values DP1, DP1 of the top 102T and / or the bottom 102B of the packed goods 102 are presented to the operator by the controller 199 via the user interface 198 in any suitable manner. The narrowing value (e.g., which informs of one or more of tilt and support surface) may be employed at least when using the controller 199 to generate a pallet building plan. The narrowing value (e.g., which informs of tilt) may be used to at least reject cases that would otherwise be misdisposed of (not pickable, not stably supportable, etc.) by automation within the logistics facility 190.

[0122] Also refer to Figure 11C, some of the case goods characteristics described herein may not be mutually exclusive. For example, as can be seen in Figure 11C , the narrowing and bulging of the case goods 102 may not be mutually exclusive (e.g., the narrowing and bulging may be inclusive of each other). In instances where more than one inclusive case goods characteristic is determined, the controller 199 is configured to identify the inclusive characteristics in accordance with the foregoing description. For example, although narrowing exists in the case goods 102 in Figure 11C , the top edge TEF generally depicts the terminus of the narrowing. The controller 199 is configured to distinguish between the generally flat surface (or generally constant spacing) of the narrowed portion of the trailing longitudinal side 102R and the variable spacing indicative of the bulge in the top 102T of the case goods 102. Here, the controller 199 is configured to determine the bulge from the top edge TE indicated by the change in spacing of the trailing longitudinal side 102R. In other respects, the controller 199 is configured to distinguish between the different case goods characteristics described herein in any suitable manner.

[0123] Referring to Figure 26 , an exemplary image depicting vertical item verification within the case goods (which is obtained from one or more of the case inspection system 180 and the flap detection system 170) is provided. The exemplary image is a generally two-dimensional image of the case goods 102; however, in other respects, a three-dimensional image may be provided. The vertical item verification provides one or more of the following: an indication of the number of different vertical items observable along an inspection axis (e.g., the lengthwise axis and / or the widthwise axis), an indication of the average width 2610 of the top (such as the bottle cap 2530) of one vertical item as observed along the inspection axis, and an indication of the average width 2620 of the gap between the tops (such as the bottle cap 2530) of adjacent vertical items as observed along the inspection axis. The above information obtained from the vertical item verification may be utilized by the controller 199 at least when generating a pallet building plan. In the illustrated example, the case goods 102 is similar to the case of the round bottle illustrated in Figure 25 .

[0124] Here, the controller 199 is configured to determine the number of vertical items within the packed goods 102 from image data obtained from one or more of the case inspection system 180 and the flap detection system 170 (in the illustrated example, there are four vertical items arranged along the longitudinal axis; however, in other aspects, three-dimensional image data from the flap detection system 180 can be employed together with or in place of two-dimensional image data from the case inspection system 180 to determine the number of vertical items along one or more of the longitudinal and width axes). It should be noted that the number of vertical items can be presented by the controller 199 to the operator in any suitable manner via the user interface 198 (it should be noted that multiple vertical items for packed goods in the form of a box are indicated as one vertical item).

[0125] The controller 199 is configured to determine the average width 2610 of the top (such as the bottle cap 2530) of one vertical item as observed along the inspection axis from image data obtained from one or more of the case inspection system 180 and the flap detection system 170 (in the illustrated example, the inspection axis is the longitudinal axis; however, in other aspects, three-dimensional image data from the flap detection system 180 can be employed together with or in place of two-dimensional image data from the case inspection system 180 to determine the average width 2610 of the top of one vertical item along one or more of the longitudinal and width axes). It should be noted that the average width 2610 of the top of one of the vertical items can be presented by the controller 199 to the operator in any suitable manner via the user interface 198 (it should be noted that the average width 2610 of the top of one of the vertical items for packed goods in the form of a box is substantially equal to the entire top surface of the box).

[0126] The controller 199 is configured to determine the average width 2620 of the gap between the tops (such as the bottle cap 2530) of adjacent vertical items as observed along the inspection axis from image data obtained from one or more of the case inspection system 180 and the flap detection system 170 (in the illustrated example, the inspection axis is the longitudinal axis; however, in other aspects, three-dimensional image data from the flap detection system 180 can be employed together with or in place of two-dimensional image data from the case inspection system 180 to determine the average width 2620 of the gap between the tops of adjacent vertical items). It should be noted that the average width 2620 of the gap between the tops of adjacent vertical items can be presented by the controller 199 to the operator in any suitable manner via the user interface 198 (it should be noted that the average width 2620 of the gap between the tops of adjacent vertical items for packed goods in the form of a box is substantially equal to zero).

[0127] As described above, the flap detection system 170 (using data from the case inspection system 180) and the profile detection system 180 determine whether the packed goods 102 that have passed through the profile detection system 180 are suitable for storage, handling, and palletizing in the logistics facility 190. For example, as described above, at least one conveyor 110, 120 advances the packed goods 102 into the logistics facility 190. The case inspection station 180 is arranged to communicate with at least one conveyor 110, 120 such that the packed goods 102 advance through the case inspection system 180. The case inspection system 180 has at least one case inspection camera (e.g., sensors / imaging devices 181, 184) that is arranged to capture an image of the shadow of each packed good 102 that is advanced through the case inspection system 180. At least one other camera 171 - 173 (e.g., the flap detection system 170) is connected to the case inspection station 180, and the at least one other camera 171 - 173 is separate from and different from the at least one sensor / imaging device 181, 184. The at least one other camera 171 - 173 is arranged to capture other case image data of each packed good 102 that is advanced through the case inspection system 180 in addition to the case image data captured by the at least one sensor / imaging device 181, 184.

[0128] Here, the processor 199P of the controller 199 is operatively coupled to at least one conveyor 110, 120. The processor 199P is also communicatively coupled to at least one sensor / imaging device 181, 184 to receive case image data from the at least one sensor / imaging device 181, 184. The processor 199P is further communicatively coupled to at least one other camera 171 - 173 to receive other case image data of each packed good 102 from the at least one other camera 171 - 173. Here, the processor 199P (and thus the controller 199) is configured to determine the predetermined characteristics (such as those described above) of each packed good 102 that determine the case form from the image of the shadow of each packed good 102 imaged by the at least one sensor / imaging device 181, 184, thereby confirming that the corresponding packed good has a case shape. The predetermined characteristics of each packed good 102 that determine the case form include one or more of the following: case length, case width, case height, the angle between case sides, box size (see Figures 13A - 20 , 25, 25A, 27, 28A, and 28B), and any other suitable physical properties of the packed goods that determine the case form, such as those described herein.

[0129] The processor 199P / controller 199 is configured to determine the compliance of the corresponding packed goods 102 with the predetermined box form adaptation characteristics (such as those described above) from other image data (e.g., from the flap detection system 170) when it is confirmed that the corresponding packed goods 102 have a box shape. As described herein, the predetermined box form adaptation characteristics inform the assembly acceptance of the corresponding packed goods 102 within a predetermined assembly space or location in the logistics facility 190 (e.g., the storage space of the storage array 190SA or other holding positions, the payload compartment of the automated transport vehicle 190ATV, the pallet load building position in the pallet building formed in the logistics facility 190, etc.).

[0130] For example, referring to Figure 28A and 28B , any given packed goods stored / disposed of by the logistics facility have corresponding expected dimensions in at least the box length, box width, and box height (note that the amount of narrowing and / or tapering, the number of individual items held, the gaps between individual items, and the width of the tops of the individual items also have expected dimensions). These expected dimensions define the predetermined box shape and form adaptation of the corresponding packed goods 102 to be inserted into the logistics facility 190, noting that each identical stock keeping unit (SKU) permitted to enter / be inserted into the logistics facility 190 has expected box dimensions that define the form adaptation of that SKU. The expected dimensions are measured from a predetermined reference datum of the packed goods 102 such that consistency exists among packed goods of the same type (i.e., the same SKU). For example, as Figure 28A illustrated, the box length dimension is measured from the length determination reference plane, and the box width dimension is measured from the width determination reference plane. The length determination reference plane and the width determination reference plane are located in the vertical planes defined, for example, by one of the lateral sides (e.g., side 102L1) and one of the longitudinal sides (e.g., side 102R). As in Figure 28BAs can be seen, the height dimension of the case is measured from a height determination reference plane defined by the bottom side 102B (or seating surface) of the case goods 102. These reference planes enable the determination of the position of the case goods, such as by (but not limited to) the controller 199, the pallet stacker 190P, and the automated transport vehicle 190ATV, for positioning the case goods 102 on, but not limited to, the storage shelves in the storage array 190SA, on the pallets in the pallet load, on the automated transport vehicle 190ATV (for the robot of the pallet stacker 190P to grasp), and on the pickface builder (any suitable case handling device of a logistics facility configured to form a pickface, including but not limited to the automated transport vehicle 190ATV and the pickface builder, such as those described in U.S. Patent No. 9,475,649, entitled "Pickface Builder for Storage and Retrieval Systems", issued on October 25, 2016, which is hereby incorporated by reference in its entirety) for the formation of the pickface, where the pickface includes more than one case goods transported / disposed of as a single unit in the logistics facility 190, etc.

[0131] The expected case length, the expected case width, and the expected case height include tolerances that allow the actual dimensions of the case goods to be a predetermined amount above and below the expected value. The tolerances can be based on the size of the storage space in the storage array 190SA, the size of the payload compartment of the automated transport vehicle 190ATV, the stability of the case goods in the pallet case construction, the storage space height limit, or any other suitable structural limitations imputed to the case goods by the structure and operation of the logistics facility 190. These expected dimensions of a given case goods type (e.g., SKU), including their tolerances, define the predetermined case form fit characteristics of the case goods 102. The determined case goods characteristics determined by the case inspection system 180 and / or the flap detection system 170 inform the actual case form fit characteristics of a given case goods inspected by the inspection system 100, and the controller 199 determines the compliance of the actual case form fit characteristics of the given case goods with the predetermined case form fit characteristics defined by the expected dimensions.

[0132] As described herein, when one or more of the determined dimensions of the stowed cargo 102 exceed the expected dimensions of the stowed cargo 102 (including any tolerances), the stowed cargo is rejected and not permitted for storage, handling, and palletizing processes in the logistics facility 190. The tolerances applied to the expected dimensions (e.g., which establish a pass or no-go type criterion for the admission of stowed cargo types into the logistics facility 190) are determined such that, in one aspect, for stowed cargo 102 that falls within approximately two standard deviations of the Gaussian distribution of the stowed cargo 102 handled by the logistics facility 190 for a given number of stowed cargo inspected by the stowed cargo inspection system 100, it is generally ensured that the stowed cargo 102 can be assembled into the storage space of the storage array 190SA or other holding positions, the payload compartment of the automated transport vehicle 190ATV, the pallet load building position in the pallet building within the logistics facility 190, and any other appropriate positions in the logistics facility 190; while in other aspects, for stowed cargo 102 that falls within approximately three standard deviations of the Gaussian distribution of the stowed cargo handled / inspected by the logistics facility 190, it is generally ensured that the stowed cargo 102 can be assembled. Here, generally ensuring the form fit or assembly of the stowed cargo that falls within approximately two standard deviations (or in some aspects, three standard deviations) of any given number of stowed cargo 102 inspected by the stowed cargo inspection system 100 provides the following for each stowed cargo 102 within the logistics facility: generally always recordable in the pick face builder, locatable on a shelf (or other suitable storage stowed cargo holding position), recordable for the pick and place of the stowed cargo by the end effector of the arm of the palletizing robot for the pallet stacker 190P, and / or generally always stackable in the pallet load formed by the pallet stacker 190P.

[0133] In operation, the flap detection system provides a binary result (i.e., open flap: yes / no) regarding the presence of an open flap, while the length, width, and height of the packed goods are measured by the profile detection system 180. As an example, when the dimensions of the packed goods 102 are recorded in the controller 199 as 8 units in width, 10 units in length, and 6 units in height and the packed goods inspection system 100 returns a result that the packed goods 102 have a width of 8 units, a length of 13 units, and a height of 6 units based on the inspection of the packed goods 102, the result of the open flap detection is true. Note that the acceptable tolerances for the dimensions of the packed goods (e.g., in the presence and absence of an open flap) can depend on the packed goods handling capabilities of downstream (i.e., after the packed goods inspection system 100) automated packed goods handling equipment. For example, Table 1 below illustrates the pass / fail rate of packed goods through the packed goods inspection system 100, where the packed goods dimension tolerance is set to 1 unit (e.g., approximately 1 inch or approximately 25 mm - the linear dimensions in Table 1 are in millimeters and the angular dimensions are in degrees), and a "1" in the pass / fail column indicates a rejected packed goods 102 and a "0" in the pass / fail column indicates an accepted packed goods 102.

[0134] Table 1:

[0135]

[0136] As can be seen in Table 1 above, the packed goods 102 are rejected when, for example, a 1-inch or 25.4-mm tolerance is employed. However, as noted above, the acceptable tolerances for the dimensions of the packed goods (e.g., in the presence and absence of an open flap) can depend on the packed goods handling capabilities of downstream (i.e., after the packed goods inspection system 100) automated packed goods handling equipment. Thus, when the downstream automated box handling equipment is capable of handling boxes with a tolerance of approximately 2 inches or 50 mm, the acceptance rate of the same packed goods increases, as shown in Table 2 below:

[0137] Table 2:

[0138]

[0139] Regarding Table 2, note that for the same packed goods, the indication of the open flap has changed from that in Table 1 because of the following condition: a minimum number of parameters must be satisfied for the open flap to be detected. In the examples of Tables 1 and 2, all parameters (note that the flap depth parameter is accounted for in the flap length and box length parameters) should be satisfied before the open flap is detected. In the case of Table 2, the increased tolerance reduces the number of detected open flaps and increases the number of accepted packed goods.

[0140] The process can also determine that the open flap extends in one or more of the length, width, and height directions of the packed cargo 102 through a comparison of the expected packed cargo size with the actual (i.e., measured) packed cargo size and the presence of the open flap. This information, along with any other appropriate information, can be presented to the operator via the user interface 198, as described herein. The flap detection system 170 supports the detection of open flaps on any of the five visible sides of the packed cargo 102 that are not located on the conveyors 110, 120. In one or more aspects, the flap detection system 170 uses the box image data to estimate the core dimensions of the packed cargo (e.g., length, width, and height without any external protrusions or open flaps of the box), even in the presence of open flaps and / or external protrusions of the box. Here, the flap detection system 170 includes any appropriate number of sensors 171-173 (such as more than two, or using mirrors to view the packed cargo from more than two angles) such that the imaging of the packed cargo side is not blocked or otherwise obstructed by the open flap. The estimation of the core dimensions of the packed cargo 102 by the flap detection system 170 can verify the acceptance or rejection of any given packed cargo by the profile detection system 180. For example, when a packed cargo is rejected by the profile detection system 180 because it exceeds the tolerance due to an open flap (e.g., one or more of the length, width, and / or height exceeds the corresponding predetermined (e.g., expected) length, width, and / or height), the flap detection system 170 verifies that the condition of exceeding the tolerance is due to the open flap and verifies whether the open flap can be handled by downstream (i.e., after the packed cargo inspection system 100) automated equipment. When a packed cargo with an open flap cannot be handled by the downstream automated equipment, the packed cargo can be rejected.

[0141] Reference Figure 1 、 1A -1C and 22, a method for inspecting a packed cargo 102 will be described in accordance with one or more aspects of the disclosed embodiments. According to the method, the packed cargo 102 is advanced through the packed cargo inspection system 100 using at least one conveyor 110, 120 ( Figure 22 , block 2200). At least one sensor 171-173 captures the box image data 1400 of each packed cargo 102 that is advanced through the packed cargo inspection system 100 using at least one conveyor 110, 120 ( Figure 14A - 14D and Figure 22 , block 2210). A processor 199P is provided ( Figure 22, the box outer protrusion 220 of the packed goods 102 from the box image data, wherein in one or more aspects, the processor 199P Figure 2A and 2B ) characterized as a box flap in an open condition Figure 22 , frame 2230), wherein the processor 199P is configured to parse the box image data 1400 and determine that the box outer protrusion 220 is a consistent flat surface 1410 Figure 14A - 14D ), and is programmed with a parameter array 199A of physical property parameters, the physical property parameters describing the box flap consistency attribute that determines the consistent flat surface 1410 defining the open box flap condition. In one or more aspects, the processor 199P parses the box image data 1400 and determines that the box outer protrusion 220 is a consistent flat surface 1410 Figure 22 , frame 2240). The processor 199P generates a physical property array 199C from the box image data 1400 for each determined consistent flat surface 1410 Figure 22 , frame 2250), and applies the parameter array 199A to the physical property array 199C to parse the consistent flat surface 1410 as an open box flap.

[0142] Now referring to Figure 1 、 1A -1C, 2B, 23A and 29, a method in an inspection device for inspecting packed goods will be described. In this method, at least one conveyor 110, 120 advances the packed goods 102 through the inspection device 100 Figure 30 , frame 3000). At least one camera 171-173 captures box image data of each packed good 102 advanced through the inspection device 100 by at least one conveyor 110, 120 Figure 30 , frame 3010). The processor 199P is provided Figure 30 , frame 3020), and receives the box image data 1400 from at least one camera 171-173. As described herein, the processor 199P is operably coupled to at least one conveyor 110, 120 and communicatively coupled to at least one camera 171-173, and the processor 199P is configured to characterize at least one of the box side depressions and box outer protrusions of the packed goods as a box flap in an open condition from the box image data 1400 of a common image of the packed goods 102 captured by at least one camera 171-173 and parsed by the processor 199P Figure 30 , frame 3040) Figure 30 , frames 3030 and 3045).

[0143] The processor 199P parses the box image data (refer to Figure 30, the frame 3040) and determines that the case exterior protrusion 220 is a consistent flat surface. The processor is programmed with a parameter array 199A of physical property parameters that describe the case flap consistency attribute that determines the consistent flat surface defining the condition of the open case flap. The processor generates a physical property array 199C from the case image data 1400 for each determined consistent flat surface ( Figure 30 , block 3050), and applies the parameter array 199A to the physical property array 199C to resolve the consistent flat surface as an open case flap.

[0144] In this method, at least one camera 171 - 173 is arranged to capture case image data 1400 of each packed item being advanced through the inspection device 100 by at least one conveyor 110, 120, such that the case image data 1400 depicts at least one of the case side recess 2300 and the case exterior protrusion 220, where at least one of the case side recess 2300 and the case exterior protrusion 220 is apparent on at least one exposed case side 102T, 102L, 102F, 120R, and the at least one exposed case side 102T, 102L, 102F, 120R is provided in each exposed case side orientation of the packed item. In this method, another imaging system (e.g., the profile detection system 180) is provided. The profile detection system 180 is separate from and different from at least one camera 171 - 173. The profile detection system 180 images the packed item 102, and this imaging is separate from and different from the imaging of the packed item 102 by at least one camera 171 - 172 for the inspection of the packed item 102 other than the detection of at least one of the case side recess and the open case flap, as described herein.

[0145] According to one or more aspects of the disclosed embodiments, there is provided an inspection device for inspecting packed goods. The inspection device includes: at least one conveyor configured to advance the packed goods through the inspection device; at least one camera arranged to capture box image data of each packed good advanced through the inspection device by the at least one conveyor; a processor operably coupled to the at least one conveyor and communicably coupled to the at least one camera to receive the box image data from the at least one camera, wherein the processor is configured to characterize box exterior protrusions of the packed goods as box flaps in an open condition from the box image data, wherein the processor is configured to analyze the box image data and determine that the box exterior protrusions are a consistent flat surface, and is programmed with an array of physical property parameters that describe box flap consistency attributes of the consistent flat surface that define the open box flap condition, and wherein the processor is configured to generate an array of physical properties from the box image data for each determined consistent flat surface and apply the array of parameters to the array of physical properties to analyze the consistent flat surface as an open box flap.

[0146] According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to image each exposed box side of each packed good advanced through the inspection device by the at least one conveyor to image the box exterior protrusions apparent on each imaged exposed box side.

[0147] According to one or more aspects of the disclosed embodiments, the imaged exposed box side is arranged such that the open box flap resolved from the box exterior protrusions apparent on the imaged exposed box side extends from the exposed box side adjacent to the conveyor seat surface on which the packed good is seated.

[0148] According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to capture the box image data of each exposed box side of each packed good advanced through the inspection device by the at least one conveyor such that the captured box image data of each packed good represents each exposed box side of the corresponding box exterior.

[0149] According to one or more aspects of the disclosed embodiments, the imaged exposed box side is arranged such that the open box flap resolved from the box exterior protrusions apparent on the imaged exposed box side extends from the exposed box side adjacent to the conveyor seat surface on which the packed good is seated.

[0150] According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to capture bin image data of each packed item being advanced through the inspection device by the at least one conveyor, such that the bin image data represents bin exterior protrusions, where the bin exterior protrusions are evident on at least one exposed bin side, and the at least one exposed bin side is provided in each exposed bin side orientation of the packed item.

[0151] According to one or more aspects of the disclosed embodiments, the at least one exposed bin side imaged by the at least one camera is arranged such that the open bin flap resolved from the bin exterior protrusions evident on the imaged at least one exposed bin side extends from the at least one exposed bin side adjacent to the conveyor seat surface on which the packed item sits.

[0152] According to one or more aspects of the disclosed embodiments, the inspection device further includes another imaging system separate from and different from the at least one camera, where the another imaging system images different characteristics of the packed item being advanced through the inspection device by the at least one conveyor, the different characteristics being different from the physical characteristics in the array of physical characteristics.

[0153] According to one or more aspects of the disclosed embodiments, the at least one camera captures the bin image data substantially simultaneously with the another imaging system imaging the different characteristics of the packed item.

[0154] According to one or more aspects of the disclosed embodiments, the inspection device further includes another imaging system separate from and different from the at least one camera, and the another imaging system images the packed item, the imaging being separate from and different from the imaging of the packed item by the at least one camera for inspection of the packed item other than the detection of the open bin flap.

[0155] According to one or more aspects of the disclosed embodiments, the another imaging system images the packed item for identification of each packed item and processor verification of the conformity of each packed item with the bin size parameters of the verified packed items.

[0156] According to one or more aspects of the disclosed embodiments, the processor is configured such that the inspection of the packed item based on the image of the packed item from the another imaging system is resolved, the resolution being separate from and different from resolving the open bin flap from the bin image data of the at least one camera.

[0157] According to one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of the exterior protrusions of the case from imaging of another imaging system that is separate from and different from the case image data captured using the at least one camera, and resolve the exterior protrusions of the case as open case flaps from the case image data of the at least one camera that is separate from and different from the image of the other imaging system.

[0158] According to one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of the exterior protrusions of the case from the case image data captured by the at least one camera, independent of an image of the packed goods captured by the other imaging system.

[0159] According to one or more aspects of the disclosed embodiments, there is provided an inspection apparatus for inspecting packed goods. The inspection apparatus includes: at least one conveyor configured to advance the packed goods through the inspection apparatus; at least one camera arranged to capture case image data of each packed good advanced through the inspection apparatus using the at least one conveyor; a processor operably coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the case image data from the at least one camera, wherein the processor is configured to characterize an exterior protrusion of the packed good as an open case flap from the case image data, wherein the processor is configured to: resolve the case image data and determine that the exterior protrusion is a consistently flat surface, and generate an array of physical characteristics of the consistently flat surface from the case image data for each determined consistently flat surface, such that the array of physical characteristics describes the consistently flat surface as a case flap, and determine that the case flap is in an open flap condition based on an array of parameter values of physical characteristic parameters.

[0160] According to one or more aspects of the disclosed embodiments, the array of parameter values of physical characteristic parameters describes a case flap consistency attribute of the consistently flat surface that defines the open case flap condition.

[0161] According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to image each exposed case side of each packed good advanced through the inspection apparatus using the at least one conveyor to image the exterior protrusions of the case that are apparent on each imaged exposed case side.

[0162] According to one or more aspects of the disclosed embodiments, the imaged exposed case side is arranged such that the open case flap resolved from the exterior protrusions of the case that are apparent on the imaged exposed case side extends adjacent to a conveyor seat surface on which the packed good is seated.

[0163] According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to capture the box image data of each exposed box side of each packed cargo that is advanced through the inspection device by the at least one conveyor, such that the captured box image data of each packed cargo represents each exposed box side outside the corresponding box.

[0164] According to one or more aspects of the disclosed embodiments, the imaged exposed box side is arranged such that the open box flap resolved from the box exterior protrusions evident on the imaged exposed box side extends from the exposed box side adjacent to the conveyor seat surface on which the packed cargo is seated.

[0165] According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to capture the box image data of each packed cargo that is advanced through the inspection device by the at least one conveyor, such that the box image data represents the box exterior protrusions, wherein the box exterior protrusions are evident on at least one exposed box side, and the at least one exposed box side is provided in each exposed box side orientation of the packed cargo.

[0166] According to one or more aspects of the disclosed embodiments, the at least one exposed box side imaged by the at least one camera is arranged such that the open box flap resolved from the box exterior protrusions evident on the imaged at least one exposed box side extends from the at least one exposed box side adjacent to the conveyor seat surface on which the packed cargo is seated.

[0167] According to one or more aspects of the disclosed embodiments, the inspection device further includes another imaging system that is separate from and different from the at least one camera, wherein the another imaging system images different characteristics of the packed cargo that is advanced through the inspection device by the at least one conveyor, and the different characteristics are different from the physical characteristics in the array of physical characteristics.

[0168] According to one or more aspects of the disclosed embodiments, the at least one camera and the another imaging system capture the box image data substantially simultaneously while imaging the different characteristics of the packed cargo.

[0169] According to one or more aspects of the disclosed embodiments, the inspection device further includes another imaging system that is separate from and different from the at least one camera, and the another imaging system images the packed cargo, and the imaging is separate from and different from the imaging of the packed cargo by the at least one camera for the inspection of the packed cargo other than the detection of the open box flap.

[0170] In accordance with one or more aspects of the disclosed embodiments, the other imaging system images the packed goods for identification of each packed good and processor verification of the compliance of each packed good with the box size parameters of the verified packed goods.

[0171] In accordance with one or more aspects of the disclosed embodiments, the processor is configured such that the packed good inspection based on the packed good image from the other imaging system is parsed, the parsing being separate from and different from parsing the open box flap from the box image data of the at least one camera.

[0172] In accordance with one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of the box exterior protrusion from imaging of the other imaging system that is separate from and different from the box image data captured by the at least one camera, and parse the box exterior protrusion as an open box flap from the box image data of the at least one camera that is separate from and different from the image of the other imaging system.

[0173] In accordance with one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of the box exterior protrusion from the box image data captured by the at least one camera, independent of the image of the packed good captured by the other imaging system.

[0174] In accordance with one or more aspects of the disclosed embodiments, a method for inspecting packed goods is provided. The method includes: advancing the packed goods through an inspection device using at least one conveyor; capturing box image data of each packed good advanced through the inspection device using the at least one conveyor using at least one camera; providing a processor operably coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the box image data from the at least one camera, and wherein the processor: characterizes the box exterior protrusion of the packed good as an open box flap from the box image data, wherein the processor is configured to parse the box image data and determine that the box exterior protrusion is a consistent flat surface, and is programmed with an array of parameter arrays of physical property parameters that describe the box flap consistency attributes of the consistent flat surface that define the open box flap condition, and wherein the processor generates an array of physical properties from the box image data for each determined consistent flat surface and applies the parameter array to the array of physical properties to parse the consistent flat surface as an open box flap.

[0175] According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to image each exposed side of each packed article that is advanced through the inspection device by the at least one conveyor, to image the external protrusions of the box that are apparent on each imaged exposed side of the box.

[0176] According to one or more aspects of the disclosed embodiments, the imaged exposed side of the box is arranged such that the open box flap resolved from the external protrusions of the box that are apparent on the imaged exposed side of the box extends from the exposed side of the box, adjacent to the conveyor seat surface on which the packed article is seated.

[0177] According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to capture the box image data of each exposed side of each packed article that is advanced through the inspection device by the at least one conveyor, such that the captured box image data of each packed article represents each exposed side of the corresponding external part of the box.

[0178] According to one or more aspects of the disclosed embodiments, the imaged exposed side of the box is arranged such that the open box flap resolved from the external protrusions of the box that are apparent on the imaged exposed side of the box extends from the exposed side of the box, adjacent to the conveyor seat surface on which the packed article is seated.

[0179] According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to capture the box image data of each packed article that is advanced through the inspection device by the at least one conveyor, such that the box image data represents the external protrusions of the box, wherein the external protrusions of the box are apparent on at least one exposed side of the box, and the at least one exposed side is provided in each exposed side orientation of the packed article.

[0180] According to one or more aspects of the disclosed embodiments, the at least one exposed side of the box imaged by the at least one camera is arranged such that the open box flap resolved from the external protrusions of the box that are apparent on the at least one imaged exposed side of the box extends from the at least one exposed side of the box, adjacent to the conveyor seat surface on which the packed article is seated.

[0181] According to one or more aspects of the disclosed embodiments, the method further comprises: providing another imaging system that is separate from and different from the at least one camera; and using the another imaging system to image different characteristics of the packed article that is advanced through the inspection device by the at least one conveyor, the different characteristics being different from the physical characteristics in the array of physical characteristics.

[0182] According to one or more aspects of the disclosed embodiments, the at least one camera captures bin image data substantially simultaneously with the other imaging system imaging the different characteristics of the packed goods.

[0183] According to one or more aspects of the disclosed embodiments, the method further includes: providing another imaging system separate from and different from the at least one camera; and using the other imaging system to image the packed goods, the imaging being separate from and different from the imaging of the packed goods by the at least one camera for inspection of the packed goods other than the detection of the open bin flaps.

[0184] According to one or more aspects of the disclosed embodiments, the other imaging system images the packed goods for identification of each packed good and processor verification of the compliance of each packed good with the bin size parameters of the verified packed goods.

[0185] According to one or more aspects of the disclosed embodiments, the processor is configured such that the inspection of the packed goods based on the image of the packed goods from the other imaging system is parsed, the parsing being separate from and different from parsing the open bin flaps from the bin image data of the at least one camera.

[0186] According to one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of the external bin protrusions from the imaging of the other imaging system separate from and different from the bin image data captured by the at least one camera, and parse the external bin protrusions as open bin flaps from the bin image data of the at least one camera separate from and different from the image of the other imaging system.

[0187] According to one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of the external bin protrusions from the bin image data captured by the at least one camera independent of the image of the packed goods captured by the other imaging system.

[0188] According to one or more aspects of the disclosed embodiments, a method for inspecting packed goods is provided. The method includes: using at least one conveyor to advance the packed goods through an inspection device; using at least one camera to capture box image data of each packed good advanced through the inspection device by the at least one conveyor; providing a processor operably coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the box image data from the at least one camera, and wherein the processor: characterizes box exterior protrusions of the packed goods that are open box flaps from the box image data; analyzes the box image data and determines that the box exterior protrusions are a consistent flat surface; and generates, for each determined consistent flat surface, an array of physical characteristics of the physical characteristics of the consistent flat surface from the box image data such that the array of physical characteristics describes the consistent flat surface as a box flap and determines that the box flap is in an open flap condition based on an array of parameter arrays of physical characteristic parameters.

[0189] According to one or more aspects of the disclosed embodiments, the array of parameter arrays of physical characteristic parameters describes a box flap consistency attribute of the consistent flat surface that determines the open box flap condition.

[0190] According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to image each exposed box side of each packed good advanced through the inspection device by the at least one conveyor to image the box exterior protrusions evident on each imaged exposed box side.

[0191] According to one or more aspects of the disclosed embodiments, the imaged exposed box side is arranged such that the open box flap parsed from the box exterior protrusions evident on the imaged exposed box side extends from the exposed box side adjacent to the conveyor seat surface on which the packed good is seated.

[0192] According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to capture the box image data of each exposed box side of each packed good advanced through the inspection device by the at least one conveyor such that the captured box image data of each packed good represents each exposed box side of the corresponding box exterior.

[0193] According to one or more aspects of the disclosed embodiments, the imaged exposed box side is arranged such that the open box flap parsed from the box exterior protrusions evident on the imaged exposed box side extends from the exposed box side adjacent to the conveyor seat surface on which the packed good is seated.

[0194] According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to capture box image data of each packed item being advanced through the inspection device by the at least one conveyor, such that the box image data represents external box protrusions, wherein the external box protrusions are apparent on at least one exposed box side, and the at least one exposed box side is provided in each exposed box side orientation of the packed item.

[0195] According to one or more aspects of the disclosed embodiments, the at least one exposed box side imaged by the at least one camera is arranged such that the open box flaps resolved from the external box protrusions apparent on the at least one imaged exposed box side extend from the at least one exposed box side adjacent to the conveyor seat surface on which the packed item is seated.

[0196] According to one or more aspects of the disclosed embodiments, the method further comprises: providing another imaging system separate from and different from the at least one camera; and imaging, using the another imaging system, different characteristics of the packed item being advanced through the inspection device by the at least one conveyor, the different characteristics being different from the physical characteristics in the array of physical characteristics.

[0197] According to one or more aspects of the disclosed embodiments, the at least one camera captures the box image data substantially simultaneously with the another imaging system imaging the different characteristics of the packed item.

[0198] According to one or more aspects of the disclosed embodiments, the method further comprises: providing another imaging system separate from and different from the at least one camera; and imaging, using the another imaging system, the packed item, the imaging being separate from and different from the imaging of the packed item by the at least one camera, for inspection of the packed item other than detection of the open box flaps.

[0199] According to one or more aspects of the disclosed embodiments, the another imaging system images the packed item for identification of each packed item and processor verification of the compliance of each packed item with the box size parameters of the verified packed items.

[0200] According to one or more aspects of the disclosed embodiments, the processor is configured such that the inspection of the packed item based on the image of the packed item from the another imaging system is resolved, the resolution being separate from and different from resolving the open box flaps from the box image data of the at least one camera.

[0201] In accordance with one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of the exterior protrusions of the case from imaging of another imaging system that is separate from and different from the case image data captured using the at least one camera, and resolve the exterior protrusions of the case into open case flaps from the case image data of the at least one camera that is separate from and different from the image of the other imaging system.

[0202] In accordance with one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of the exterior protrusions of the case from the case image data captured by the at least one camera, independent of an image of the packed goods captured by the other imaging system.

[0203] In accordance with one or more aspects of the disclosed embodiments, there is provided an inspection device for inspecting packed goods. The inspection device includes: at least one conveyor configured to advance the packed goods through the inspection device; at least one camera arranged to capture case image data of each packed good advanced through the inspection device using the at least one conveyor; a processor operably coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the case image data from the at least one camera; and wherein the processor is configured to characterize at least one of a case side depression and an exterior protrusion of the packed goods as an open case flap from the case image data generated from a common image of the packed goods captured by the at least one camera.

[0204] In accordance with one or more aspects of the disclosed embodiments, the processor is configured to analyze the case image data and determine that the exterior protrusion of the case is a uniformly flat surface, and is programmed with an array of physical property parameters that describe the case flap consistency attributes of the uniformly flat surface that define the open case flap condition.

[0205] In accordance with one or more aspects of the disclosed embodiments, the processor is configured to generate an array of physical properties from the case image data for each determined uniformly flat surface and apply the array of parameters to the array of physical properties to resolve the uniformly flat surface into an open case flap.

[0206] In accordance with one or more aspects of the disclosed embodiments, the at least one camera is arranged to image each exposed case side of each packed good advanced through the device using the at least one conveyor to image at least one of the case side depressions and the exterior protrusions that are apparent on each imaged case side from the common image of each imaged case side.

[0207] In accordance with one or more aspects of the disclosed embodiments, the at least one camera is arranged to capture bin image data of each packed article being advanced through the inspection device by the at least one conveyor, such that the bin image data depicts at least one of the bin side indentations and the bin exterior protrusions, wherein at least one of the bin side indentations and the bin exterior protrusions is evident on at least one exposed bin side, and the at least one exposed bin side is provided in each exposed bin side orientation of the packed article.

[0208] In accordance with one or more aspects of the disclosed embodiments, the at least one exposed bin side imaged by the at least one camera is arranged such that at least one of the bin side indentations and the bin exterior protrusions resolved from at least one of the bin side indentations and the bin exterior protrusions evident on the imaged at least one exposed bin side extends from the at least one exposed bin side adjacent to the conveyor seat surface on which the packed article is seated.

[0209] In accordance with one or more aspects of the disclosed embodiments, the inspection device further includes another imaging system separate from and different from the at least one camera, and the another imaging system images the packed article, the imaging being separate from and different from the imaging of the packed article by the at least one camera for inspection of the packed article other than for detection of at least one of the bin side indentations and the open bin flaps.

[0210] In accordance with one or more aspects of the disclosed embodiments, the another imaging system images the packed article for identification of each packed article and processor verification of the conformity of each packed article with the bin size parameters of the verified packed articles.

[0211] In accordance with one or more aspects of the disclosed embodiments, the processor is configured such that the inspection of the packed article based on the image of the packed article from the another imaging system is resolved, the resolution being separate from and different from resolving at least one of the bin side indentations and the open bin flaps from the bin image data of the at least one camera.

[0212] In accordance with one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of at least one of the bin side indentations and the bin exterior protrusions of the packed article from imaging of the another imaging system separate from and different from the bin image data captured by the at least one camera, and resolve at least one of the bin side indentations and the bin exterior protrusions from the bin image data of the at least one camera separate from and different from the image of the another imaging system as corresponding bin indentations and open bin flaps.

[0213] According to one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of at least one of the box side depressions and the box exterior protrusions on the side of the packed goods from the box image data captured by the at least one camera, independent of the image of the packed goods captured by the other imaging system.

[0214] According to one or more aspects of the disclosed embodiments, there is provided an inspection device for inspecting packed goods. The inspection device includes: at least one conveyor configured to advance the packed goods through the inspection device; at least one camera arranged to capture box image data of each packed goods advanced through the inspection device by the at least one conveyor; a processor operably coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the box image data from the at least one camera, wherein: the processor is configured to characterize at least one box top or at least one box side having a depression condition from the box image data of the packed goods captured by the at least one camera, wherein the processor is programmed to parse an inward variation of the at least one box top or the at least one box side with respect to a predetermined planar consistency characteristic of the box top or box side from the image data; and the processor is configured to determine, from the image data for the presence of each parsed inward variation, a physical characteristic that describes the depression condition of the at least one box top or the at least one box side.

[0215] According to one or more aspects of the disclosed embodiments, the processor is configured to parse the box image data and determine that the at least one box top or the at least one box side has an inward variation, and is programmed with an array of parameter arrays of physical characteristic parameters that describe the inward variation attributes of the inward variation that defines the depression condition.

[0216] According to one or more aspects of the disclosed embodiments, the processor is configured to generate an array of physical characteristics from the box image data for each determined inward variation and apply the array of parameter arrays to the array of physical characteristics to parse the inward variation as a depression condition.

[0217] According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to image each exposed box side of each packed goods advanced through the inspection device by the at least one conveyor to image the depression condition apparent on each imaged box side from the common image of each imaged box side.

[0218] According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to capture box image data of each packed item that is advanced through the inspection device by the at least one conveyor, such that the box image data represents a dent condition, wherein the dent condition is apparent on at least one exposed box side, and the at least one exposed box side is provided in each exposed box side orientation of the packed item.

[0219] According to one or more aspects of the disclosed embodiments, the at least one exposed box side imaged by the at least one camera is arranged such that the dent condition resolved from the dent condition apparent on the imaged at least one exposed box side extends adjacent to the conveyor seat surface on which the packed item is located.

[0220] According to one or more aspects of the disclosed embodiments, the inspection device further includes another imaging system that is separate from and different from the at least one camera, and the another imaging system images the packed item, the imaging being separate from and different from the imaging of the packed item by the at least one camera, for inspection of the packed item other than detection of the dent condition.

[0221] According to one or more aspects of the disclosed embodiments, the another imaging system images the packed item for identification of each packed item and processor verification of the compliance of each packed item with the box size parameters of the verified packed items.

[0222] According to one or more aspects of the disclosed embodiments, the processor is configured such that inspection of the packed item based on the image of the packed item from the another imaging system is resolved, the resolution being separate from and different from resolving the dent condition from the box image data of the at least one camera.

[0223] According to one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of a packed item with a dent condition from imaging of the another imaging system that is separate from and different from the box image data captured by the at least one camera, and resolve the dent condition as a box dent from the box image data of the at least one camera that is separate from and different from the image of the another imaging system.

[0224] According to one or more aspects of the disclosed embodiments, the processor is configured to determine the presence of a packed item with a dent condition from the box image data captured by the at least one camera, independent of the image of the packed item captured by the another imaging system.

[0225] According to one or more aspects of the disclosed embodiments, there is provided an inbound conveyor system for guiding a boxed cargo in a logistics facility. The system includes: at least one conveyor configured to push the boxed cargo into the logistics facility; a box inspection station arranged to communicate with the at least one conveyor such that the boxed cargo is advanced through the box inspection station, the box inspection station having at least one box inspection camera configured to capture an image of a shadow of each boxed cargo advanced through the box inspection station; at least another camera connected to the box inspection station, separate from and different from the at least one box inspection camera, and arranged to capture other box image data of each boxed cargo advanced through the box inspection station in addition to the box image data captured by the at least one box inspection camera; and a processor operably coupled to the at least one conveyor, communicatively coupled to the at least one box inspection camera for receiving the box image data from the at least one box inspection camera, and communicatively coupled to the at least another camera for receiving the other box image data of each boxed cargo from the at least another camera, wherein the processor is configured to determine a predetermined characteristic of each boxed cargo that determines the box form from the image of the shadow of each boxed cargo imaged by the at least one box inspection camera, thereby confirming that the corresponding boxed cargo has a box shape, and wherein the processor is configured to, after confirming that the corresponding boxed cargo has the box shape, determine the conformity of the corresponding boxed cargo with the predetermined box form adaptation characteristics from the other image data.

[0226] According to one or more aspects of the disclosed embodiments, the predetermined box form adaptation characteristics inform the acceptance of the corresponding boxed cargo within a predetermined assembly space or position in a storage array of the logistics facility.

[0227] According to one or more aspects of the disclosed embodiments, the predetermined assembly space or position is a pallet load building position in a pallet build formed in the logistics facility.

[0228] According to one or more aspects of the disclosed embodiments, the predetermined box form adaptation characteristics are an inward bulge or depression of at least one side of the box shape of the corresponding boxed cargo relative to a flat box side.

[0229] According to one or more aspects of the disclosed embodiments, the predetermined characteristics of each boxed cargo that determine the box form include one or more of box length, box width, box height, an angle between box sides, and box size.

[0230] In accordance with one or more aspects of the disclosed embodiments, the processor includes: an image acquisition component configured to acquire more than one digital image from the case inspection station for each packed item being advanced through the case inspection station; and an image combiner configured to selectively combine a plurality of acquired digital images different from the more than one digital image into a combined image, based on a reduction in the spatial intensity of a continuous input light beam below a first threshold during a duration of the more than one digital image among the acquired digital images.

[0231] In accordance with one or more aspects of the disclosed embodiments, the processor is configured to confirm the presence of a packed item based on a reduction in the spatial intensity of a continuous input light beam below a second threshold, thereby discerning the presence of a semi-transparent shrink wrap on a product disposed within the packed item.

[0232] In accordance with one or more aspects of the disclosed embodiments, the image combiner is configured to selectively combine the acquired digital images into a potential product combined image, wherein a plurality of pixels digitized in an image having a reduced intensity below a first predetermined threshold define an image width greater than a second threshold.

[0233] In accordance with one or more aspects of the disclosed embodiments, the image combiner is configured to selectively combine the acquired digital images into the combined image, wherein a plurality of pixels digitized across sequential images having a reduced intensity below a first predetermined threshold and a second threshold represent a predetermined combined image length.

[0234] In accordance with one or more aspects of the disclosed embodiments, the at least one conveyor is configured to advance the packed item at a propulsion rate, and the image acquisition component is configured to acquire the digital images at an acquisition rate proportional to the propulsion rate of the packed item.

[0235] In accordance with one or more aspects of the disclosed embodiments, the image acquisition rate is synchronized by using an encoder or by a stepper motor drive circuit.

[0236] In accordance with one or more aspects of the disclosed embodiments, the image acquisition component includes an image buffer storage.

[0237] In accordance with one or more aspects of the disclosed embodiments, the at least one case inspection camera is configured to determine an ambient light intensity from a sample buffer of the buffered images.

[0238] In accordance with one or more aspects of the disclosed embodiments, the processor is configured to determine dimensions from the combined image of: a first shape optimally fitting in the combined image, a second shape circumscribing the combined image, and a difference between the first shape and the second shape.

[0239] In accordance with one or more aspects of the disclosed embodiments, the processor is configured to determine an orientation angle of the packed goods with respect to the at least one conveyor from the combined image.

[0240] In accordance with one or more aspects of the disclosed embodiments, the processor is configured to determine a distance of the packed goods from a side of the at least one conveyor from the combined image.

[0241] In accordance with one or more aspects of the disclosed embodiments, the case inspection station is configured to identify the presence of debris on the input window of the at least one case inspection camera based on common pixels of the same intensity across multiple digital images.

[0242] In accordance with one or more aspects of the disclosed embodiments, a method in an inspection apparatus for inspecting packed goods is provided. The method includes: advancing packed goods through the inspection apparatus using at least one conveyor; capturing case image data of each packed good advanced through the inspection apparatus using the at least one conveyor using at least one camera; and providing a processor and using the processor to receive the case image data from the at least one camera, wherein the processor is operably coupled to the at least one conveyor and communicatively coupled to the at least one camera, and the processor is configured to characterize at least one of a case side indentation and a case exterior protrusion of the packed goods as an open case flap from the case image data generated from a combined image of the packed goods captured by the at least one camera.

[0243] In accordance with one or more aspects of the disclosed embodiments, the processor parses the case image data and determines that the case exterior protrusion is a consistently flat surface, and the processor is programmed with an array of physical property parameters that describe case flap consistency attributes of the consistently flat surface that define an open case flap condition.

[0244] In accordance with one or more aspects of the disclosed embodiments, the processor generates an array of physical properties from the case image data for each determined consistently flat surface and applies the array of parameters to the array of physical properties to parse the consistently flat surface as an open case flap.

[0245] According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to image each exposed side of each packed article that is advanced through the device by the at least one conveyor, to image at least one of the side recesses and external protrusions of the box that are apparent on each imaged side of the box from the common image of each imaged side of the box.

[0246] According to one or more aspects of the disclosed embodiments, the at least one camera is arranged to capture box image data of each packed article that is advanced through the inspection device by the at least one conveyor, such that the box image data represents at least one of the side recesses and external protrusions of the box, wherein at least one of the side recesses and external protrusions of the box is apparent on at least one exposed side of the box, and the at least one exposed side is provided in each exposed side orientation of the packed article.

[0247] According to one or more aspects of the disclosed embodiments, the at least one exposed side of the box imaged by the at least one camera is arranged such that at least one of the side recesses and the box flaps in the open condition that are resolved from at least one of the side recesses and external protrusions of the box that are apparent on the at least one imaged exposed side of the box extends from the at least one exposed side of the box adjacent to the conveyor seat surface on which the packed article is located.

[0248] According to one or more aspects of the disclosed embodiments, the method further includes imaging the packed article using another imaging system that is separate from and different from the at least one camera, the imaging being separate from and different from the imaging of the packed article by the at least one camera, for inspection of the packed article other than for detection of at least one of the side recesses and the open box flaps.

[0249] According to one or more aspects of the disclosed embodiments, the other imaging system images the packed article for identification of each packed article and processor verification of the compliance of each packed article with the box size parameters of the verified packed articles.

[0250] According to one or more aspects of the disclosed embodiments, the processor is configured such that the inspection of the packed article based on the image of the packed article from the other imaging system is resolved, the resolution being separate from and different from resolving at least one of the side recesses and the open box flaps from the box image data of the at least one camera.

[0251] In accordance with one or more aspects of the disclosed embodiments, the processor determines the presence of at least one of the box side depressions and the box exterior protrusions of the packed goods from imaging of another imaging system that is separate from and different from the box image data captured using the at least one camera, and resolves at least one of the box side depressions and the box exterior protrusions into corresponding box depressions and open box flaps from the box image data of the at least one camera that is separate from and different from the image of the other imaging system.

[0252] In accordance with one or more aspects of the disclosed embodiments, the processor determines the presence of at least one of the box side depressions and the box exterior protrusions on the packed goods side from the box image data captured by the at least one camera, independent of the image of the packed goods captured by the other imaging system. Although a reference is made herein to a “vision system,” aspects of the disclosed embodiments are not limited to any single camera system operating in the millimeter wave, infrared, visual, microwave, X-ray, gamma ray, etc. spectra, nor to any combination of camera systems. Although a compound camera may be employed, separate spectrum-specific cameras may also be employed plural or in combination. Any reference to packed goods including food material (or other content) is incidental and is not intended to limit the scope of any of the appended claims.

[0253] It should be understood that the foregoing description is merely illustrative of aspects of the disclosed embodiments. Various alternatives and modifications may be envisioned by those skilled in the art without departing from the aspects of the disclosed embodiments. Accordingly, aspects of the disclosed embodiments are intended to cover all such alternatives, modifications, and variations that fall within the scope of any of the appended claims. Additionally, the mere fact that different features are recited in mutually different dependent or independent claims does not indicate that a combination of these features cannot be used advantageously, and such combination is still within the scope of the aspects of the disclosed embodiments.

Claims

1. An inspection device for inspecting boxed goods, the inspection device comprising: at least one conveyor configured to advance the boxed cargo through the inspection device; at least one camera arranged to capture case image data of each cased shipment advanced through the inspection apparatus using the at least one conveyor; a processor operably coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the bin image data from the at least one camera, wherein the processor is configured to characterize, from the case image data, a case external protrusion of the cased goods as a case flap in an open condition, wherein the processor is configured to parse the case image data and determine that the case external protrusion is a uniform planar surface, and is programmed with a parameter array of physical property parameters describing case flap conformity attributes that determine the uniform planar surface defining an open case flap condition, and Wherein the processor is configured to generate a physical property array from the box image data for each determined conforming planar surface and apply the parameter array to the physical property array to resolve the conforming planar surface into an open box flap.

2. An inspection device according to claim 1, wherein the at least one camera is arranged to image each exposed box side of each boxed cargo that is advanced through the inspection device using the at least one conveyor to image the box external protrusions that are evident on each imaged exposed box side.

3. An inspection device according to claim 2, wherein the imaged exposed box side is arranged so that the open box flap resolved from the box exterior protrusions evident on the imaged exposed box side extends from the exposed box side adjacent to the conveyor seat surface on which the boxed goods are seated.

4. The inspection device according to claim 1, wherein the at least one camera is arranged to capture the box image data of each exposed box side of each boxed cargo that is advanced through the inspection device using the at least one conveyor, so that the captured box image data of each boxed cargo reflects each exposed box side of the corresponding box exterior.

5. An inspection device according to claim 4, wherein the imaged exposed box side is arranged so that the open box flap resolved from the box exterior protrusions evident on the imaged exposed box side extends from the exposed box side adjacent to the conveyor seat surface on which the boxed goods sit.

6. An inspection device according to claim 1, wherein the at least one camera is arranged to capture box image data of each boxed cargo that is advanced through the inspection device using the at least one conveyor, so that the box image data reflects the box external protrusions, wherein the box external protrusions are evident on at least one exposed box side, and the at least one exposed box side is arranged in each exposed box side orientation of the boxed cargo.

7. The inspection apparatus of claim 6, wherein the at least one exposed box side imaged by the at least one camera is arranged such that the open box flap resolved from the box exterior protrusions evident on the at least one exposed box side imaged extends from the at least one exposed box side adjacent to a conveyor seat surface on which the boxed goods sit.

8. The inspection device of claim 1 , further comprising another imaging system separate from and different from the at least one camera, wherein the other imaging system images different characteristics of packaged goods that are advanced through the inspection device using the at least one conveyor, the different characteristics being different from the physical characteristics in the array of physical characteristics.

9. The inspection apparatus of claim 8, wherein the at least one camera captures case image data substantially simultaneously with the another imaging system imaging the different characteristics of the cased goods.

10. The inspection apparatus of claim 1 , further comprising another imaging system separate from and distinct from the at least one camera, and wherein the another imaging system images the boxed goods, the imaging being separate from and distinct from the at least one camera imaging of the boxed goods, for inspection of the boxed goods other than detection of the open box flaps.

11. The inspection device of claim 10, wherein the another imaging system images the cased shipments for identification of each cased shipment and processor verification of compliance of each cased shipment with case size parameters of the verified cased shipments.

12. The inspection apparatus of claim 10, wherein the processor is configured such that inspection of cased cargo based on cased cargo images from the another imaging system is resolved separately and distinct from resolving the open case flaps from the case image data from the at least one camera.

13. An inspection device according to claim 10, wherein the processor is configured to determine the presence of the external protrusion of the box from imaging of the other imaging system that is separate from and different from the box image data captured using the at least one camera, and to resolve the external protrusion of the box as an open box flap from the box image data of the at least one camera that is separate from and different from the images of the other imaging system.

14. The inspection device of claim 10, wherein the processor is configured to determine the presence of the case external protrusion from the case image data captured by the at least one camera independently of the image of the cased goods captured by the other imaging system.

15. An inspection device for inspecting boxed goods, the inspection device comprising: at least one conveyor configured to advance the boxed cargo through the inspection device; at least one camera arranged to capture case image data of each cased shipment advanced through the inspection apparatus using the at least one conveyor; a processor operably coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the bin image data from the at least one camera, wherein the processor is configured to characterize, from the case image data, case exterior protrusions of the cased goods as open case flaps, wherein the processor is configured to: parsing the box image data and determining that the box external protrusion is a uniformly flat surface, and A physical property array of physical properties of the conforming planar surface is generated from the box image data for each determined conforming planar surface, such that the physical property array describes the conforming planar surface as a box flap, and the box flap is determined to be in an open flap condition based on a parameter array of physical property parameters.

16. The inspection apparatus of claim 15, wherein the parameter array of physical property parameters describes box flap conformity attributes that determine the conforming planar surface that defines the open box flap condition.

17. A method for inspecting packaged goods, the method comprising: utilizing at least one conveyor to advance the packaged goods through the inspection equipment; utilizing at least one camera to capture case image data of each cased shipment advanced through the inspection apparatus utilizing the at least one conveyor; providing a processor operably coupled to the at least one conveyor and communicatively coupled to the at least one camera to receive the bin image data from the at least one camera, and wherein the processor: characterizing a case external protrusion of the cased goods as a case flap in an open condition from the case image data, wherein the processor is configured to parse the case image data and determine that the case external protrusion is a uniform planar surface and is programmed with a parameter array of physical characteristic parameters describing case flap conformity attributes that determine the uniform planar surface defining an open case flap condition, and Wherein the processor generates a physical property array from the box image data for each determined conforming planar surface and applies the parameter array to the physical property array to resolve the conforming planar surface into an open box flap.

18. A method according to claim 17, wherein the at least one camera is arranged to image each exposed box side of each boxed cargo that is advanced through the inspection device using the at least one conveyor to image the box external protrusions that are evident on each imaged exposed box side.

19. The method of claim 18, wherein the imaged exposed box side is arranged such that the open box flap resolved from the box exterior protrusions evident on the imaged exposed box side extends from the exposed box side adjacent to a conveyor bed surface on which the boxed goods sit.

20. The method of claim 17, wherein the at least one camera is arranged to capture the box image data of each exposed box side of each boxed cargo that is advanced through the inspection device using the at least one conveyor, such that the captured box image data of each boxed cargo reflects each exposed box side of the corresponding box exterior.

Images