Information processing system, feature point extraction method, and control program

Abstract

This information processing system comprises: a comparison unit 513 for comparing first feature point information for a web in first inspection data with second feature point information for the web in second inspection data, and extracting feature points that are the same in the first inspection data and the second inspection data; an analysis unit 514 for generating relationship information indicating the relationship between a coordinate position with respect to the entire web and the difference value of coordinates in the first inspection data and the second inspection data for each of the plurality of feature points extracted by the comparison unit; and an output unit 516 for outputting the relationship information.

Description

Information processing system, feature point extraction method, and control program

[0001] The present invention relates to an information processing system, a feature point extraction method, and a control program.

[0002] Liquid crystal display devices are increasingly being used in large-screen televisions and large monitors, and as a result, there is a demand for wider films to be used on the display surfaces of liquid crystal display devices. For example, wide films of 2000 mm or more are in demand. Furthermore, in order to anticipate substrate loss (film loss) and reduce transportation costs, there is a demand for the production of long film rolls with winding lengths of 1000 m or more, and even 3000 m or more.

[0003] In the post-processing of products using webs such as film as a base material, when defects or other quality issues occur, it is necessary to determine whether the defect occurred in the upstream process, i.e., during the production of the web and was originally present on the web, or whether it occurred during the post-processing process. If it is not possible to clearly determine that the defect occurred in the post-processing process, improvements to the upstream process may be required. In response to requests for improvement, the shipping standards for the upstream process may become stricter than necessary, resulting in over-specification. Furthermore, in order to prevent quality issues, even though it is unclear how the downstream process will be affected, the shipping standards for the web may be set too strictly based on expectations. Such cases also constitute over-specification. Over-specification leads to reduced yields, increased costs, and is ecologically undesirable, and is undesirable for both the upstream and downstream process operators.

[0004] It is necessary to distinguish whether the defect was originally present on the web or whether it occurred during a post-processing step. In doing so, it is necessary to match the coordinate system on the web in the previous process with the coordinate system in the post-process.

[0005] The following Patent Document 1 discloses a technique for synchronizing the inspection results of a first and second inspection device in an optical film inspection system. In this inspection system, the inspection results of both devices are synchronized by using an encoder signal that indicates the distance between the first inspection device and the second inspection device located downstream in the transport direction, and the amount of film movement.

[0006] JP 2016-161576 A

[0007] The technology in Patent Document 1 synchronizes inspection results based on the mutual distance and movement distance between the inspection devices, but cannot achieve synchronization when the film expands or contracts.Furthermore, synchronization cannot be achieved when two inspection devices are wound into a roll of film and an offline process of unwinding the roll is included.

[0008] The present invention has been made in consideration of the above circumstances, and aims to efficiently collect information that is useful for process improvement and setting shipping standards both when manufacturing a web and in the manufacturing process in which post-processing is performed using the web.

[0009] The above object of the present invention can be achieved by the following means.

[0010] (1) An information processing system comprising: an acquisition unit that acquires first inspection data from a first manufacturing process in which a web is manufactured or a manufactured web is post-processed, and second inspection data from a second manufacturing process in which post-processing using the web is performed after the first manufacturing process; a comparison unit that compares first feature point information of the web in the first inspection data with second feature point information of the web in the second inspection data, and extracts identical feature points in the first and second inspection data; an analysis unit that generates relationship information indicating the relationship between the coordinate difference values ​​in the first inspection data and the second inspection data for each of the multiple feature points extracted by the comparison unit and the coordinate positions on the entire web; and an output unit that outputs the relationship information.

[0011] (2) The information processing system according to (1), wherein the relationship information is a graph showing the relationship between coordinate difference values ​​and overall coordinate positions.

[0012] (3) The information processing system according to (1) or (2), wherein the relationship information is statistical information indicating the relationship between the coordinate difference value and the overall coordinate position.

[0013] (4) The information processing system described in (1) above further includes a receiving unit that receives a correction amount for the coordinates of the first inspection data and / or the second inspection data, and the comparing unit corrects the coordinates of the feature points with the correction amount received by the receiving unit, then compares the first feature point information of the web in the first inspection data with the second feature point information of the web in the second inspection data, and extracts identical feature points in the first and second inspection data.

[0014] (5) The information processing system described in (4) above, wherein the reception unit receives the correction amount after the output unit displays the relationship information, and in response to the reception unit receiving the correction amount, the comparison unit again extracts the same feature points, the analysis unit generates the relationship information, and the output unit again displays the relationship information.

[0015] (6) The information processing system described in (1) above, wherein the relationship information is a scatter diagram and a regression equation that represent the relationship between coordinate difference values ​​and overall coordinate positions, and further includes an extraction unit that classifies the feature points according to the distance from the feature points in the scatter diagram to the regression equation.

[0016] (7) The information processing system described in (1) above, wherein the relationship information includes a correlation coefficient indicating the relationship between the coordinate difference value and the overall coordinate position, or a variance of the difference value, and the analysis unit generates an alert when the absolute value of the correlation coefficient is less than or equal to a first predetermined threshold value, or when the variance is greater than or equal to a second predetermined threshold value, and the output unit issues an alert.

[0017] (8) A method for extracting feature points of a web, comprising: (a) acquiring first inspection data in a first manufacturing process for manufacturing a web or post-processing a manufactured web; (b) acquiring second inspection data in a second manufacturing process for performing post-processing using the web, which is performed after the first manufacturing process; (c) comparing first feature point information of the web in the first inspection data with second feature point information of the web in the second inspection data; (d) extracting identical feature points in the first and second inspection data based on the comparison result of (c); (e) generating relationship information indicating the relationship between a difference value between the coordinates of each of the multiple feature points extracted in (d) in the first inspection data and the second inspection data and the coordinate position on the entire web; and (f) outputting the relationship information generated in (e).

[0018] (9) The feature point extraction method according to (7), wherein the relationship information is a graph showing the relationship between coordinate difference values ​​and overall coordinate positions.

[0019] (10) A control program for causing a computer to execute the extraction method described in (7) or (8) above.

[0020] The information processing system of the present invention includes an acquisition unit that acquires first inspection data from a first manufacturing process in which a web is manufactured or a manufactured web is post-processed, and second inspection data from a second manufacturing process in which a post-processing process using the web is performed after the first manufacturing process. The information processing system also includes a comparison unit that compares first feature point information of the web in the first inspection data with second feature point information of the web in the second inspection data and extracts identical feature points in the first and second inspection data, an analysis unit that generates relationship information indicating the relationship between the coordinate difference values ​​between the first inspection data and the second inspection data for each of the feature points extracted by the comparison unit and the coordinate positions of the entire web, and an output unit that outputs the relationship information. This allows efficient collection of information useful for process improvement and setting shipping standards both during web manufacturing and during post-processing manufacturing processes using the web.

[0021] Advantages and features provided by one or more embodiments of the present invention will be more fully understood from the following detailed description and the accompanying drawings, which are for illustrative purposes only and are not intended to limit the present invention.

[0023] FIG. 1 is a schematic diagram of a film roll production line.

[0024] FIG. 2 is a schematic top view of the stretching, drying, and trimming processes of the production line of FIG. 1.

[0025] FIG. 3 is a schematic diagram of an inspection device.

[0026] FIG. 4 is a schematic diagram of an inspection device.

[0027] FIG. 5 is a schematic diagram of an application example of an information processing system according to an embodiment of the present invention.

[0028] FIG. 6 is a table for explaining extracted first to third type feature points.

[0029] FIG. 7 is a block diagram showing a schematic configuration of an information processing system.

[0030] FIG. 8 is an example of various data stored in a storage unit.

[0031] FIG. 9 is an example of an inspection data DB stored in a storage unit.

[0032] FIG. 10 is a flowchart showing a process for generating first inspection data performed in a first manufacturing process.

[0033] FIG. 11 is a flowchart showing a process for generating second inspection data performed in a second manufacturing process.

[0034] FIG. 12 is a flowchart showing a process for extracting feature points performed in an information processing system.

[0035] FIG. 13 is an example of an operation screen for accepting an expansion / contraction ratio.

[0036] FIG. 14 is a schematic diagram for explaining the process for extracting feature points.

[0037] FIG. 15 is a subroutine flowchart showing comparison process 1 of step S35. 1 is an example of a probability density function showing the positions and intensities of feature points calculated by kernel density estimation; FIG. 2 is an example of a corresponding point list; FIG. 3 is an example of a distribution map as relationship information; FIG. 4 is an example of a distribution map as relationship information; FIG. 5 is an example of a distribution map as relationship information; FIG. 6 is an example of a distribution map as relationship information; FIG. 7 is an example of a distribution map as relationship information; FIG. 8 is an example of a distribution map as relationship information; FIG. 9 is an example of an operation screen for accepting correction amounts; FIG. 10 is a subroutine flowchart showing comparison processing 2 of step S50;

[0022] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. However, the scope of the present invention is not limited to the disclosed embodiments. In the description of the drawings, the same elements are denoted by the same reference numerals, and duplicate explanations will be omitted. Furthermore, the dimensional proportions in the drawings are exaggerated for the convenience of explanation and may differ from the actual proportions.

[0023] In this embodiment, the web refers to a sheet-like material, including a resin film and a metal film. In the following description, the web refers to a long resin film, such as a film roll, and is processed onto the film roll. Processing also includes applying a coating liquid and overlaying another film-like material.

[0024] First, a production line for a film roll 80 will be described with reference to Figures 1 and 2. Figure 1 is a schematic diagram showing a production line for a film roll. The production line shown in Figures 1 and 2 exemplifies film production by a solution casting method, but is not limited to this and film production by a melt extrusion method may also be used.

[0025] As shown in FIG. 1, the film roll manufacturing apparatus 1000 includes a casting section 01, a first drying section 02, a stretching section 03, a trimming section 05, a second drying section 06, and a winding section 07 (also referred to as a winding device).

[0026] In the film roll manufacturing apparatus 1000, an inspection device 90 is disposed between multiple processes. The inspection device 90 monitors the surface of the film F8 being transported on the production line, photographs the film surface, and analyzes the resulting frame images to detect the transport state of the film F8. The configuration of the inspection device 90 will be described later ( FIG. 3A , etc.). In FIG. 1, the outline arrow indicates the transport direction of the film, etc.

[0027] The casting unit 01 includes a mirror-finished metal casting belt (hereinafter referred to as the belt) 01a, which is an endless support that runs endlessly (in the direction of the arrow in the figure), and a die 01b that casts a dope, which is a resin dissolved in a solvent, onto the belt 01a. In order to stabilize the dope film flowing out from the die 01b, a decompression chamber (not shown) may be provided upstream of the die 01b in the belt transport direction, and a pressurization chamber (not shown) may be provided downstream of the die 01b.

[0028] The peeling roll 01d peels off the casting film 01c formed by casting on the belt 01a, to produce an unstretched film F8.

[0029] The first drying section 02 (first drying process) has a drying box 02a having a dry air intake 02b and an exhaust 02c, and a pair of upper and lower transport rolls 02d that are composed of multiple sets for transporting the film F8.

[0030] In the first drying section 02, it is possible to adjust the amount of solvent contained in the unstretched film F8 before it enters the stretching section 03 (stretching step). The adjustment of the amount of solvent is performed by changing the drying temperature and conveying speed in the first drying section 02 using the control device 08.

[0031] (Stretching section 03, trimming section 05) Figure 2 is a schematic top view of the stretching process (also referred to as the tenter process), drying process, and trimming process of the production line in Figure 1. In Figures 2, 3A, etc., the vertical direction is the Z direction, the conveying direction of the film F8 is the Y direction, and the direction perpendicular to the conveying direction, the width direction of the film F8, is the X direction. The Y direction or conveying direction is also referred to as MD (Machine Direction). The X direction to the width direction is also referred to as TD (Transverse Direction) or left-right direction. The Y direction is also referred to as the longitudinal direction, and the width direction is also referred to as the width direction in its paired relationship with the longitudinal direction.

[0032] The stretching unit 03 has an MD stretching unit 03a and a TD stretching unit 03b. The stretching unit 03 stretches the unstretched film F8 transported from the first drying unit 02. As shown in Figure 2, the stretching unit 03 grips both side edges of the heated film F8 with multiple pairs of left and right gripping units 301. The stretching unit 03 includes the gripping units 301, chains, a drive unit, closers, openers, etc. (Components other than the gripping units 301 are not shown).

[0033] In the upstream MD stretching section 03a (MD stretching step), the unstretched film F8 is transported while accelerating as it is transported downstream, and the transport speed in the transport direction gradually increases (indicated by the black arrow in Figure 2). As a result, in the MD stretching step, the unstretched film F8 is transported while being stretched in the MD direction.

[0034] In the next stage, the film F8 and the like are conveyed by the gripping units 301 in the TD stretching unit 03b (TD stretching process). The gripping units 301 are, for example, clips, and the left and right gripping units 301 are connected to, for example, an endless chain. The chain, wound around a sprocket, is rotated by a drive unit, causing the gripping units 301 to move in the conveyance direction and the like. A closer is disposed at the most upstream side of the TD stretching process in the stretching unit 03, and an opener is disposed at the most downstream side. When the gripping units 301 reach the closer position, the open gripping units 301 are sequentially closed, and when they reach the opener position, they are sequentially opened. The closed gripping units 301 grip the side edges of the film F8 and convey it. In this TD stretching unit 03b (TD stretching process), the pair of left and right gripping units 301 gripping the film F8 and the like move in the conveyance direction and gradually move outward in the width direction (black arrows). As a result, in the TD stretching step, the distance (spacing) between the pair of gripping parts 301 in the width direction gradually increases, and the film F8 etc. gripped by these gripping parts is transported while being stretched in the TD direction.

[0035] In addition, an oblique stretching step other than the TD stretching step may be applied to this stretching step. The TD stretching step stretches the film in a direction parallel to the width direction. That is, in the TD stretching step, film F8 expands at an angle of 0° with the width direction. On the other hand, in the oblique stretching step, in order to adjust the optical properties of the film, both ends of the heated film are held by multiple gripping devices and the film is stretched in an oblique direction at an angle of 40 to 50° with the width direction (referred to as "oblique stretching"). In this case, the cooling step may also include a heat-relaxing step in which the stretched film is continuously transported while being heat-treated to relax stress.

[0036] The trimming unit 05 (trim process) has a cutting unit 05a and a recovery unit 05b. The cutting unit 05a includes two slitters 5110L and 5110R, one on each side, and multiple rollers 5120. The slitters 5110L and 5110R are, for example, circular or dish-shaped blades supported on rotatable shafts and rotated by a drive unit (not shown). The slitters 5110L and 5110R may rotate in the same direction as the film F8 at the cutting position, at a speed approximately equal to the conveyance direction, or may rotate in the opposite direction. The two slitters 5110L and 5110R separate the film F8 from the cutting position into a central portion (film F8) and trimmed films F801 and F802 (also called selvages) on both sides.

[0037] The central portion of the film F8 is the area that will become the product, and its width ranges, for example, from 1,000 mm to 2,500 mm. The widths (also referred to as trim widths) of the trimmed films F801 and F802 are both several tens to several hundred millimeters (e.g., 170 mm). The central portion of the film F8 is transported downstream in the transport direction and supplied to the subsequent winding process. Meanwhile, the trimmed films F801 and F802 are turned 90 degrees downward by roller 5120 and transported, and are collected by the downstream collection unit 05b. The collection unit 05b has a rotary cutter and a suction duct (both not shown). The transported trimmed films F801 and F802 are cut by the rotary cutter 522 into small chips of several millimeters in size, which are collected in a dust box in a downstream vacuum cleaner. In addition, if the inspection device 90 is placed before the trim process, the trim width may be input, and coordinate conversion may be performed from the photographed data in accordance with the trim width in preprocessing (step S32 in FIG. 11 described below).

[0038] The central portion of the film F8 is transported to the downstream winding section 07. A knurling process may be performed by providing a knurling step between the trimming section 05 and the winding section 07. In the knurling step, knurls are formed on both ends of the trimmed film F8.

[0039] The second drying section 06 (second drying step) has the same basic configuration as the first drying section 02, so a description thereof will be omitted.

[0040] (Winding section 07) The winding section 07 has a winder 07a that winds up the film F8, both ends of which have been knurled in the trimming section 05, an entrained air amount control device 07b, a contact or non-contact linear encoder 07c for detecting the running speed of the stretched film F8, a winding shaft rotation speed measuring device 07d, a tension control device 07e, and a thickness measuring device 6f.

[0041] 1 etc., in the casting unit 01, a raw material resin is dissolved in a solvent, and various additives such as a plasticizer, an ultraviolet absorber, a deterioration inhibitor, a slip agent, and a release accelerator are added as needed to prepare a dope, which is then extruded from a die 01b onto an endless belt 01a that moves endlessly. A casting film formed by casting on the belt 01a is removed from the solvent to a certain extent on the endless support, and then peeled from the belt. The film is then passed through a drying unit and a stretching unit 03 by various conveying means, where both ends are trimmed and knurled as appropriate, and then wound around a take-up shaft in a winding unit 07 to produce an optical film.

[0042] The material of the film F8 produced as shown in Figures 1 and 2 is not particularly limited, but typical examples include polycarbonate resin, polysulfone resin, acrylic resin, polyolefin resin, cyclic olefin resin, polyether resin, polyester resin, polyamide resin, polysulfide resin, unsaturated polyester resin, epoxy resin, melamine resin, phenol resin, diallyl phthalate resin, polyimide resin, urethane resin, polyvinyl acetate resin, polyvinyl alcohol resin, styrene resin, cellulose acetate resin, and vinyl chloride resin. Furthermore, for example, the width of film F8 is preferably 1000 mm to 3200 mm, taking into consideration productivity, quality, and the like. The thickness is preferably 15 μm to 500 μm, taking into consideration quality, handling, and the like.

[0043] The length of the optical film F8 in the film roll 80 wound around the winding shaft 82 (see FIG. 1; the winding shaft is also called the winding core) is preferably 2000 m to 8000 m, taking into consideration productivity, winding quality, etc. The winding length indicates a value calculated from the speed and time. The winding speed is, for example, 100 m / min.

[0044] The inspection device 90 photographs the film or the like and generates image data. In the example shown in Fig. 1, a plurality of inspection devices 90 are arranged before and after each process, including the stretching process, of the film production line. In Fig. 1, the inspection devices 90 are arranged so as to photograph the surface of the film F8 immediately after the casting process (casting section 01), immediately after the drying process (first drying section 02), and immediately after the trimming process (trimming section 05). The configuration of the inspection device 90 will be described below with reference to Figs. 3A to 3C.

[0045] (Inspection device 90) The following types of devices are available for detecting irregularities on the surface of a transparent body such as film F8 as an object to be inspected, as well as bubbles, cracks, distortions in the internal structure, and the like inside the transparent body: (1) A transmission type inspection device that detects defects in the object to be inspected by irradiating the object with light and receiving the light that has passed through the object to be inspected. (2) A reflection type inspection device that detects defects in the object to be inspected by receiving the light reflected from the object to be inspected.

[0046] Furthermore, for both the transmissive and reflective types, there are bright-field inspection devices that receive unscattered light from the surface and dark-field inspection devices that receive scattered light, depending on the relative positions of the camera's optical axis, light source, and object under inspection. In a bright-field inspection device, if there is no defect, there is no scattering of light, so light from the light source enters the light detection means without being blocked. If there is a defect, the light is blocked by the defect and does not enter the light detection means. Therefore, the defect is observed as a dark dot or streak against a bright background. In contrast, in a dark-field inspection device, if there is no defect, there is no scattering of light, so light does not enter the light detection means. However, if there is a defect, the light is scattered by the defect and enters the light detection means. Therefore, the defect is observed as a bright dot or streak against a dark background. The inspection device 90 in this embodiment may be of any type. It is preferable, but not limited to, that the first inspection data and the second inspection data be acquired by the same type of inspection device.

[0047] (Reflection-Type Inspection Device) FIG. 3A is a schematic diagram showing the configuration of a reflection-type inspection device 90 as viewed from the width direction (X direction). FIG. 3B is a schematic diagram showing the configuration of the inspection device 90 as viewed from the transport direction (Y direction). The inspection device 90 includes a light source 91, a camera 92 as an optical sensor, an image analysis unit 93 as a data processing device, and a memory unit 94. The inspection device 90 optically inspects feature points (hereinafter simply referred to as defects) that occur on the film F8 during transport. In the inspection device 90, the camera 92 optically inspects the film F8 in the film roll 80 and generates image data as inspection data. The image data includes not only still images but also video data consisting of a time-series of consecutive still images. Furthermore, feature points may be extracted directly from signal data without converting the data into image data. The number of cameras, the angle of view, and the distance to the film surface of the camera 92 are set so that the entire width of the film F8 is the inspection area (capture range). The number of cameras is determined so that multiple cameras can be arranged in the width direction when a single camera cannot adequately capture the entire width of the film. FIG. 3B illustrates an example in which two cameras 92 are arranged in the width direction (X direction). The image analysis unit 93 may combine multiple images obtained by continuous shooting with one camera 92 to generate a single image data piece containing the entire film surface of the film roll 80, or may store multiple image data pieces in the storage unit 94 in association with the shooting times. Similar image data pieces obtained by multiple cameras 92 arranged in the width direction may also be combined. The image analysis unit 93 can determine the longitudinal position of the film F8 by referencing the stored transport speed (winding speed or unwinding speed) and the shooting times associated with the image data. In the following description, it is assumed that multiple image data pieces obtained by continuous shooting are stored for one film roll 80 in association with the shooting times. The image analysis unit 93 generates defect information by analyzing the image data. The inspection device 90 inspects the long film F8 for defects that occur during the manufacturing process, such as while the film F8 is being wound.

[0048] The light source 91 irradiates the inspection area of ​​the film F8 with light. The light source 91 irradiates the light uniformly across the width of the rolled film F8 (a direction perpendicular to the longitudinal direction of the film F8 and parallel to the film surface). Here, "uniform" means that the illuminance on the film F8 is substantially uniform across the width of the film F8 (e.g., the difference between the maximum and minimum values ​​is equal to or less than a predetermined value).

[0049] The camera 92 is an optical sensor that optically reads the inspection area of ​​the film F8. The camera 92 includes an imaging element such as a charge coupled device (CCD) or a complementary metal oxide semiconductor (CMOS), a lens, and the like. The camera 92 is an area sensor that generates two-dimensional image data from the output signals of the imaging elements. The camera 92 detects diffused light that is irradiated by the light source 91 and reflected from the inspection area of ​​the film F8. Here, either a color camera or a black and white camera (monochrome camera) may be used as the camera 92.

[0050] The one or more cameras 92 have a shooting range that spans the entire width of the film F8, and in one shooting session, the entire width of the film F8 is simultaneously read. The cameras 92 may be those that detect light in the visible light range or those that detect light in the infrared range.

[0051] Furthermore, it is desirable that the contrast between the signal values ​​corresponding to the irradiated areas on the film F8 that are irradiated with light from the light source 91 and the signal values ​​corresponding to the non-irradiated areas that are not irradiated with light from the light source 91 be equal to or greater than a predetermined value in the output signal from the camera 92. In other words, it is desirable that only the areas on the film F8 that are irradiated with light from the light source 91 (irradiated areas) appear bright.

[0052] The contrast is expressed as the difference or ratio between two values ​​to be processed (here, the signal value corresponding to the irradiated portion and the signal value corresponding to the non-irradiated portion), and the more different the two values ​​are, the greater the contrast. In order to increase the contrast between the irradiated portion and the non-irradiated portion, it is desirable to use a light source 91 that is powerful and has high directivity.

[0053] Here, "strong" means that when the illuminance at an irradiation distance of 50 mm is E50, the illuminance E50 is 50,000 lx or more. Also, "highly directional" means that when the illuminance at an irradiation distance of 50 mm is E50 and the illuminance at an irradiation distance of 100 mm is E100, the relationship (E50-E100) / E50<0.5 is satisfied.

[0054] The image analysis unit 93 is composed of a CPU, RAM, etc., and reads out various processing programs stored in the storage unit 94, loads them into the RAM, and performs various processes in cooperation with the programs.

[0055] The storage unit 94 is configured with an HDD, SSD (Solid State Drive), etc., and stores various processing programs, data necessary for executing the programs, etc. The storage unit 94 also stores captured image data (inspection data) in association with the time of capture. The storage unit 94 also stores the winding speed (e.g., 100 m / min) of the film roll manufacturing apparatus 1000 or the feeding conditions (e.g., 30 m / min) of the film F8 in the product manufacturing apparatus 2000. These winding speeds and feeding conditions may be included in the inspection list of the inspection DB (see Table T3 in FIG. 8 ).

[0056] The image analysis unit 93 detects characteristic points (positions and intensities) of defects and the like on the film F8 by performing data processing on the output signal of the camera 92 (optical sensor). The data processing includes image processing of image data obtained from the output signal of the camera 92, defect determination processing for determining defects based on the image-processed data, and quantitative evaluation processing for quantitatively evaluating the defects based on the image-processed data.

[0057] (Relative Positions of Camera 92 and Light Source 91) The camera 92 may be positioned so as to receive specularly reflected light emitted from the light source 91 (in the case of a bright-field inspection method that receives non-scattered light).

[0058] The camera 92 may be positioned to avoid receiving specularly reflected light from the light source 91 (in the case of a dark-field inspection method that receives scattered light). In other words, it is preferable to position the camera 92 at a position where it receives diffused light reflected from the object under inspection.

[0059] 3C shows an example of a transmission-type inspection device 90. In this manner, a transmission-type inspection device 90 may be employed in which the light source 91 is disposed opposite the camera 92 with the film F8 sandwiched therebetween.

[0060] 4 is a schematic diagram showing an application example of an information processing system 50 according to this embodiment. As shown in FIG. 4, the information processing system 50 is connected to terminal devices 70 and the like in factories A and B via a network for mutual communication. The network is a communication line such as a data communication network. Some networks may use a wired LAN, a wireless LAN, or the like (for example, a LAN conforming to the IEEE 802.11 standard).

[0061] The terminal device 70 is, for example, a PC (personal computer). For example, the terminal device 70 is a PC used by an employee of a manufacturing company that operates Factory A and Factory B.

[0062] The above-described film roll manufacturing apparatus 1000 is installed in factory A. Factory A is operated or managed by, for example, a film manufacturer. Factory A carries out a first manufacturing process for manufacturing a film roll 80. The film surface of the film roll 80 is inspected by an inspection device 90.

[0063] Factory B is equipped with product manufacturing equipment 2000. Factory B is operated or managed, for example, by a coating manufacturer or the like (hereinafter also referred to as a user company or user). Each factory B is operated by multiple user companies. Factory B manufactures products using film rolls 80 shipped and transported from factory A. Factory B performs a first or second manufacturing process, which is post-processing by unwinding a film (film F8, described below) from the film roll 80 and coating or superimposing or adhering it with another film.

[0064] In this embodiment, in a typical example, the process of manufacturing a film (web) is referred to as the first manufacturing process, and the post-processing performed at factory B using this manufactured film is referred to as the second manufacturing process. For example, the post-processing process includes a stretching process, or a stretching process and a coating process in which a functional layer is applied to the surface. In the second manufacturing process, the film surface of the film roll 80 is also inspected by the inspection device 90.

[0065] As a non-typical example of this embodiment, when multiple post-processing steps are performed on the film manufactured in factory B, the first post-processing step may be referred to as the first manufacturing process, and the later post-processing step may be referred to as the second manufacturing process. Alternatively, the film roll 80 manufactured in factory A may be unwound and post-processed in a later step. In this case, the step of manufacturing the film roll 80 may be referred to as the first manufacturing process, and the later post-processing step performed in the same factory A after unwounding the film roll 80 may be referred to as the second manufacturing process. The second manufacturing process performed in factory A includes stretching and drying steps.

[0066] (Outline of Feature Point Extraction Process) Details of the feature point extraction process will be described later, but an outline of the feature point extraction process will be described below with reference to Fig. 4. In the following, as a typical example, the process of manufacturing a film (web) will be described as the first manufacturing process, and post-processing performed at factory B using this manufactured film will be described as the second manufacturing process.

[0067] In the first manufacturing process at factory A, during product inspection, the film is optically inspected by inspection device 90, and inspection data (also referred to as failure data or defect data) is generated. Specifically, inspection data (hereinafter referred to as first inspection data) including feature point information (feature points, positions, and intensities) is generated by analyzing image data obtained by photographing the surface of the film. Information processing system 50 acquires the first inspection data from terminal device 70 at factory A (step S1).

[0068] Here, feature points refer to defects on the film, and are generated by analyzing image data. Image analysis may involve extracting, as feature points, pixels whose pixel values ​​deviate by a predetermined amount from the average value of the surrounding pixels (the difference is greater than or equal to a predetermined amount) in image data captured from a film surface using known techniques. Alternatively, feature points may be calculated using the "image processing for generating feature points" technique described below. In many cases, dozens to thousands of feature points are generated from one or more image data captured from a single film roll 80 (total length several kilometers). Defects include both defects that could result in product defects and minor defects that do not result in product defects. Feature points include defects related to poor adhesion when film pieces are bonded together (by ultrasonic welding, for example) and axial irregularities. Feature point information includes size and position (x-y coordinates). Alternatively, feature point information may be obtained by grouping (clustering) multiple nearby feature points together. The image processing for generating feature points will be described later.

[0069] The film roll 80 manufactured in Factory A is transported to Factory B. In the second manufacturing process at Factory B, the film roll 80 is optically inspected by an inspection device 90 during product inspection, generating inspection data. Image data obtained by photographing the film surface is analyzed to generate inspection data containing feature points (hereinafter referred to as second inspection data). The information processing system 50 acquires the second inspection data from the terminal device 70 at Factory B (Step S2). It is preferable that the inspection device 90 at Factory A (first manufacturing process) and the inspection device 90 at Factory B (second manufacturing process) are the same, i.e., have the same measurement system and the same measurement conditions, but this is not limited to this. Factories A and B may have different required performance, quality, and product specifications (hereinafter referred to as product specifications, etc.), and an inspection device 90 with an appropriate measurement system and measurement conditions may be used depending on the respective product specifications, etc.

[0070] The information processing system 50 performs a feature point extraction process by comparing the first and second inspection data for the same film roll 80 (step S3). Specifically, the information processing system 50 performs the feature point extraction process by comparing feature points at corresponding positions on the film surface in the first and second inspection data. In this specification, detecting feature points from image data is referred to as "generating feature points." Comparing the first and second inspection data and classifying the feature points into one of the following first to third type feature points is referred to as "extracting feature points."

[0071] 5 is a table illustrating the first to third type feature points extracted by the feature point extraction process. A plurality of feature points generated from the inspection data of one film roll 80 may be classified into each of the first to third type feature points. For example, some of the hundreds of feature points may be extracted as first type feature points, some as second type feature points, and the rest as third type feature points.

[0072] (First type feature points) First type feature points are feature points that are present in the first inspection data but not present in the second inspection data. First type feature points are feature points that disappear in the second manufacturing process (e.g., the coating process). These first type feature points are feature points that do not need to be managed in the first manufacturing process. In this case, the manufacturing conditions that cause the first type feature points to occur may be subject to relaxed standards in the first manufacturing process.

[0073] (Second-type feature points) Second-type feature points are feature points that are not present in the first inspection data but are present in the second inspection data. Second-type feature points are feature points that newly appear in the second manufacturing process. Because these second-type feature points are feature points that originate in the second manufacturing process, they can be used to improve the second manufacturing process.

[0074] (Third-class feature points) Third-class feature points are feature points that exist in both the first inspection data and the second inspection data. These third-class feature points are feature points that originate from the first manufacturing process and require management. Because these third-class feature points originate from the first manufacturing process, they can be used to improve the first manufacturing process.

[0075] The information processing system 50 may feed back the feature point extraction results to users such as employees of Factory A and Factory B (step S4). For example, the extraction results are sent to the terminal device 70 in response to access from the terminal device 70 of the user of the manufacturer of the target film roll 80 and the terminal device 70 of the user to whom the film roll 80 was delivered. This is an overview of the feature point extraction process. More detailed content of the process will be described later.

[0076] (Information Processing System 50) The information processing system 50 will be described below with reference to Figs. 6 to 8. Fig. 6 is a block diagram showing a schematic configuration of the information processing system 50. The information processing system 50 is, for example, a server. As shown in Fig. 6, the information processing system 50 includes a control unit 51, a storage unit 52, and a communication unit 53.

[0077] (Control unit 51) The control unit 51 has a CPU and memories such as RAM, ROM, etc. The CPU is a control circuit configured with a multi-core processor or the like that controls the above-mentioned units and executes various arithmetic processing in accordance with a program, and each function of the information processing system 50 is realized by the CPU executing the corresponding program.

[0078] The control unit 51 functions as an acquisition unit 511 and a reception unit 512 in cooperation with the communication unit 53. The control unit 51 also functions as a comparison unit 513, an analysis unit 514, an extraction unit 515, and an output unit 516. The acquisition unit 511 acquires first and second inspection data obtained by inspections in the first and second manufacturing processes. The reception unit 512 receives input of a correction amount from a user. The reception unit 512 may also receive input of an expansion / contraction ratio from a user. Here, the correction amount includes X direction, Y direction, θ direction, r direction, and front / back correction. In the following description, the correction amount is assumed to be X direction, Y direction, and θ direction. In the following description, the received expansion / contraction ratio and correction amount are collectively referred to as the correction amount, etc. The comparison unit 513 extracts feature points from each of the first and second inspection data and performs a comparison process using the received correction amount, etc. The comparison unit 513 searches for corresponding feature points between the first and second test data through a comparison process. In the comparison process, the comparison unit 513 generates feature point descriptors (descriptor 2, described below) for the two test data (image data), performs feature point matching between the test data using the feature point descriptors, and outputs the comparison results (a corresponding point list shown in FIG. 16, described below). The analysis unit 514 calculates an index indicating the relationship (hereinafter referred to as relationship information) using the corresponding point list. The relationship information includes graphs and statistical information such as averages, regression equations, variances, standard deviations, and correlation coefficients. Graphs include scatter plots, histograms, Pareto charts, bubble charts, and the like. Regression equations include regression lines and polynomial regressions of second or higher order. In addition to simple regression, regression methods such as multiple regression and logistic regression may be used for the regression equation (regression model). The main extraction unit 515 extracts (classifies) first to third type feature points using the comparison result. The output unit 516 transmits the feature point extraction results to the terminal device 70 or displays them on a display unit (not shown) in response to a request from the terminal device 70, etc.

[0079] (Storage Unit 52) ​​The storage unit 52 is a large-capacity auxiliary storage device that stores various programs including an operating system and various data. For example, a hard disk, a solid state drive, a flash memory, a ROM, etc. are used as the storage. The storage unit 52 stores a user list, a lot list, an inspection data DB, etc. Of these, the user list and lot list are managed and registered by an administrator who accesses the terminal device 70. For example, this administrator is a person in charge of the relevant department of the manufacturer that operates Factory A.

[0080] (User List) FIG. 7 shows an example of various data stored in the storage unit 52. Table T1 shown in FIG. 7 is an example of a user list. The user list stores user IDs, user names, contact information, etc. In addition, each user is assigned access rights to a search data DB (inspection database), and is granted access rights to various data (inspection data, extracted data, etc.) related to the film roll 80 (identified by lot ID) that the user is involved in.

[0081] (Lot List) Table T2 in Fig. 7 is an example of a lot list. The lot list records the lot ID assigned to each film roll, the product name (also called the type), the delivery destination user ID (orderer), multiple manufacturing conditions, size (width, length, thickness), manufacturing date, etc.

[0082] (Inspection Data DB) FIG. 8 is an example of an inspection DB (database) stored in the storage unit 52. The inspection data DB stores data related to the inspection of various film rolls 80, such as the first and second inspection data and feature point extraction results as shown in FIG. 8. As described above, the first inspection data is data obtained from the inspection in the first manufacturing process. The second inspection data is data obtained from the inspection in the second manufacturing process. The feature point extraction results are data generated by the information processing system 50 using the first and second inspection data.

[0083] 8 is an example of an inspection list registered in the inspection data DB. The inspection list stores an inspection ID, a lot ID, an inspection device ID, inspection data, inspection date and time, etc.

[0084] Table T4 in Fig. 8 shows an example of the contents of inspection data (inspection ID: i0101) in the inspection list. The inspection data includes feature point IDs that are automatically assigned consecutive numbers to each feature point, and feature point descriptors 1 and 2 (hereinafter simply referred to as descriptor 1, etc.) for each feature point ID.

[0085] Descriptor 1 is information about a feature point alone, and records its XY coordinate position and intensity. Intensity is the rank of the feature point, which will be described later. Intensity information may also include information about the feature point's size (diameter, area) and brightness. The XY coordinate position is based on the origin of the film surface (e.g., the left end of the leading edge). X is the coordinate in the width direction of the film, and can range, for example, from 0 to 3000 mm depending on the film size (see Table T2). Y is the coordinate in the length direction of the film, and can range, for example, from 0 to 10000 m depending on the film size. Descriptor 1 is generated by the image analysis unit 93 of the inspection device 90.

[0086] Descriptor 2 is peripheral information, such as vector or array information representing peripheral information such as relationships with other feature points. For example, SIFT features may be used as the descriptor, or a probability density function of feature points calculated by kernel density estimation may be used as the descriptor. Descriptor 2 is mainly generated by the comparison unit 513.

[0087] Table T5 in FIG. 8 is an example of extraction result data (hereinafter simply referred to as extracted data). The extracted data records the inspection IDs of the original first and second inspection data and the extraction results for each feature point. The extraction results (Types 1 to 3) are classified as shown in FIG. 5 above. The integrated feature point IDs are automatically assigned consecutive numbers, and integrated feature points are generated corresponding to feature points present in either or both of the first and second inspection data. The number of integrated feature point IDs is greater than or equal to the number of first inspection and second inspection feature point IDs. The extracted data is updated as correction amounts and other information are input. This is because descriptors 1 and 2 are updated by receiving correction amounts and other information (steps S402 and S502 in FIGS. 14 and 15), as described below, and the updated descriptors 1 and 2 are compared.

[0088] Note that multiple first and second inspection data sets may be generated for one lot ID by multiple inspection devices. For example, in the second manufacturing process, the film roll 80 in its original wound state is inspected (photographed), and multiple second inspection data sets are generated by inspections in several downstream processes. In this case, the information processing system 50 may generate multiple feature point extraction result data sets for one first inspection data set and multiple second inspection data sets (one-to-many). Furthermore, the user may be able to select which second inspection data sets are associated with which data sets (for example, buttons b1 and b2 in FIG. 12 , which will be described later).

[0089] (Communication Unit 53) The communication unit 53 also serves as an interface for network connection with an external device such as a PC.

[0090] (Generation Process of First and Second Inspection Data) Hereinafter, the generation process of the first and second inspection data performed in the first and second manufacturing processes will be described with reference to Fig. 9 and Fig. 10. Fig. 9 is a flowchart showing the generation process of the first inspection data performed in the first manufacturing process.

[0091] (Process for Generating First Inspection Data) (Step S11) In the typical example described above, in the first manufacturing process, the film roll 80 is manufactured by the film roll manufacturing apparatus 1000.

[0092] (Step S12) The inspection device 90 photographs the film and stores the image data. The inspection device 90 is the one described with reference to FIG. 3A and the like.

[0093] (Step S13) The image analysis unit 93 performs image processing, which will be described below, on the image data to generate a plurality of feature points.

[0094] (Image Processing for Generating Feature Points) The image analysis unit 93 acquires two-dimensional image data generated by the camera 92 and stored in the storage unit 94 .

[0095] The image analysis unit 93 performs data processing on the image data (inspection data) acquired from the camera 92 .

[0096] The image analysis unit 93 divides the image data into a plurality of regions. For example, the image analysis unit 93 divides the image data into n regions (e.g., several to several tens) in the width direction (hereinafter referred to as regions a1 to an).

[0097] Next, the image analysis unit 93 acquires image data of one area a1 and performs mathematical processing on the image data of area a1. Appropriate mathematical processing is prepared depending on the type of defect to be detected (gauge band, vertical wrinkle, diagonal wrinkle, uneven bright spot, light leak, etc.).

[0098] The mathematical processing includes preprocessing, enhancement processing, signal processing, image feature extraction, and the like.

[0099] Preprocessing includes the following: Image trimming, Low-pass filter, high-pass filter, Gaussian filter, median filter, bilateral filter, Morphological transformation, color transformation (L*a*b*, sRGB, HSV, HSL), contrast adjustment, noise removal, restoration of blurred / shaky images, mask processing, Hough transform, projection transformation, etc.

[0100] Examples of enhancement processing include a Sobel filter, a Scharr filter, a Laplacian filter, a Gabor filter, and a Canny method.

[0101] Signal processing includes the following: Basic statistics (maximum, minimum, average, median, standard deviation, variance, quartile), square root of the sum of squares, difference, sum, product, ratio, distance matrix calculation, differential and integral calculus, threshold processing (binarization, adaptive binarization, etc.), Fourier transform, wavelet transform, peak detection (peak value, number of peaks, half-width, etc.), etc.

[0102] Examples of image feature extraction include template matching and SIFT features.

[0103] Next, the image analysis unit 93 performs threshold processing on the values ​​(feature amounts) calculated by mathematical processing of the image data of the area a1. The threshold processing is a process for determining whether or not the defect is a target defect based on a predetermined defect determination threshold, and for determining the rank (intensity) of the defect.

[0104] In threshold processing, determining the presence and type of defects corresponds to “defect determination processing.” In threshold processing, classifying defects into multiple ranks according to the thresholds corresponds to “quantitative evaluation processing.”

[0105] For example, defects are classified into multiple ranks for a parameter (feature) that takes a value between 1 and 100. For example, the ranks are classified according to the size (diameter or area) of the defect. Alternatively, the ranks classified by size may be further subdivided according to the parameter value.

[0106] The image analysis unit 93 performs similar processing on areas other than the area a1.

[0107] After processing each of the regions a1 to an, the image analysis unit 93 integrates the results for each of the regions a1 to an, and data processing ends. Specifically, the image analysis unit 93 generates data that associates the rank of the detected defect with the occurrence position (x and y coordinates) for each region (each position in the width direction of the film F8).

[0108] After the data processing, the image analysis unit 93 stores the results of the data processing in the storage unit 94. The image analysis unit 93 obtains processing results by performing this type of data processing on each of the multiple image data obtained by inspecting one film roll 80. By aggregating these processing results, inspection data such as that shown in Table T4 in FIG. 8 is generated.

[0109] (Step S14) Terminal device 70 in the first manufacturing process sends inspection data including the plurality of feature point information obtained in the processes up to step S13 to information processing system 50. Acquisition unit 511 of information processing system 50 stores the acquired inspection data in the inspection data DB of storage unit 52 as first inspection data.

[0110] (Generation Process of Second Inspection Data) FIG. 10 is a flowchart showing the generation process of second inspection data performed in the second manufacturing process.

[0111] (Step S21) In the second manufacturing process, after the first manufacturing process, the product manufacturing apparatus 2000 performs post-processing using the film roll 80 to manufacture a product using the film F8.

[0112] (Step S22) The inspection device 90 photographs the surface of the film F8 before post-processing, or during or after post-processing, and stores the image data.

[0113] (Step S23) The image analysis unit 93 stores the generated inspection data including the feature point information of the plurality of feature points in the storage unit 94 by the same process as in step S13.

[0114] (Step S24) Terminal device 70 in the second manufacturing process sends inspection data including multiple pieces of feature point information obtained in the processes up to step S23 to information processing system 50. Acquisition unit 511 of information processing system 50 stores the acquired inspection data as second inspection data in the inspection data DB of storage unit 52. The second inspection data is described by feature point IDs and feature point descriptors 1 and 2, similar to the first inspection data shown in Table T4.

[0115] (Feature Point Extraction Processing) Hereinafter, the feature point extraction processing executed in the information processing system 50 will be described with reference to Figs. 11 to 18. Fig. 11 is a flowchart showing the feature point extraction processing. Fig. 12 is an example of an operation screen displayed on the terminal device 70. Fig. 13 is a schematic diagram for explaining the feature point extraction processing.

[0116] The information processing system 50 starts the processing from step S31 onward in response to a start instruction from the user via the operation screen of the terminal device 70, or when the second inspection data is registered in the inspection data DB of the storage unit 52 and a pair of first and second inspection data is obtained. FIG. 12 shows an example of the operation screen 701 displayed on the terminal device 70. After selecting a lot, the user selects the first and second inspection data from among the multiple inspection data linked to that lot using buttons b1 and b2. The second inspection data is inspection data obtained in a process downstream of the first inspection data. In this embodiment, the description will be given assuming that a stretching process is performed between the positions where the first inspection data and the second inspection data were collected.

[0117] (Step S31) The acquisition unit 511 acquires the same lot, i.e., a pair of first and second inspection data, from the inspection data DB. The same lot is linked by the lot ID assigned to the inspection ID. The same lot is linked by the lot ID assigned to the inspection ID. Note that a branch ID or a new lot ID may be assigned to the lot ID in one of the processes, and the lot ID may not correspond one-to-one, but may correspond one-to-n or n-to-1. For example, a 3,000-meter film lot may be divided into three 1,000-meter pieces in a subsequent process in a pre-process. In this case, a branch ID of the lot ID or a new lot ID is assigned in the subsequent process. Conversely, two or three film rolls may be spliced ​​in a pre-process to form a single film for use in a subsequent process. In this case, the pre-process has two or three lot IDs, and the subsequent process has one lot ID. In either case, the correspondence between the lot IDs in each process is described in the lot list (see FIG. 7).

[0118] (Steps S32 and S33) The comparison unit 513 performs preprocessing on the first inspection data under the first condition, and performs preprocessing on the second inspection data under the second condition.

[0119] 13 , as preprocessing for the second condition, the comparison unit 513 performs preprocessing of inverting the Y coordinate (up and down) of the second inspection data to match any differences between winding (first manufacturing process) and unwinding (second manufacturing process). Furthermore, in the second manufacturing process, the comparison unit 513 performs preprocessing of inverting the X coordinate (left and right) of the second inspection data (or the first inspection data) depending on information indicating whether the image capture area of ​​the camera 92 is set to the front or back side of the film F8. Furthermore, in the second manufacturing process, if the film F8 expands or contracts due to the settings of the heating temperature and tension in post-processing, and if the expansion / contraction rate can be estimated in advance, the comparison unit 513 performs coordinate conversion on the first inspection data or the second inspection data using the expansion / contraction rate received by the reception unit 512.

[0120] Furthermore, the comparison unit 513 performs at least one of the following noise removal processes on the first and second inspection data, which are included in the first and second conditions: (1) Removal of low-rank feature points; (2) Removal of extremely small feature points; (3) Removal of continuous dots; and (4) Removal of concentrated dots in the width direction, which occur particularly at the leading and trailing ends of film F8.

[0121] (Step S34) The accepting unit 512 accepts the expansion / contraction rate from the user. For example, the accepting unit 512 accepts the expansion / contraction rate input via an operation screen 701 displayed on the terminal device 70 as shown in FIG. 12. The user can input any value within a predetermined range (e.g., 50 to 300%) using buttons b3 and b4 on the numeric keypad. The accepting unit 512 accepts the input of the expansion / contraction rate in the Y direction (longitudinal direction) via button b3 from the user. The accepting unit 512 also accepts the input of the expansion / contraction rate in the X direction (widthwise direction) via button b4 from the user. The operation screen 701 in FIG. 12 shows a state in which 140% has been entered for both. If the value is greater than 100%, it is assumed that the film in the second inspection data has stretched more than the film in the first inspection data.

[0122] 12 shows an example in which the stretching unit 03 performs TD stretching in the X direction and MD stretching in the Y direction, and accordingly receives expansion / contraction ratios for each of the X direction and the Y direction. This is not limiting, and for example, when the stretching unit 03 performs an oblique stretching process, the receiving unit 512 may receive a stretching ratio for the oblique stretching. In this case, the receiving unit 512 receives an input of a stretching angle value within a predetermined range (40 to 50°).

[0123] (Step S35) The comparison unit 513 searches for feature points in one of the test data that are identical to or correspond to feature points in the other test data by comparison process 1, and matches the feature points with each other. Fig. 14 is a subroutine flowchart showing the processing of step S35.

[0124] (Step S401) The comparison unit 513 shifts the position of one of the feature points in the first and second inspection data according to the expansion / contraction ratio received in step S34. That is, the comparison unit 513 converts the coordinate system. In the following description, the comparison unit 513 shifts the feature points in the first inspection data according to the expansion / contraction ratio. For example, in the input example shown in FIG. 12 , the comparison unit 513 converts the Y coordinate of each feature point in the first inspection data into a value multiplied by the expansion / contraction ratio, with the origin (0) as the base. Here, the origin is the leading position (start of winding) of film F8 during production of the film roll 80 (the end when unwound). The comparison unit 513 also converts the X coordinate of each feature point in the first inspection data into a value multiplied by the expansion / contraction ratio, with the center point as the base. That is, the first inspection data is transformed so that it expands on both sides of the center point. Here, the center point is the center position of the film in the width direction in the first inspection data. As another example, in the case of oblique stretching, the comparison unit 513 calculates the stretch rate in the X direction and the stretch rate in the Y direction corresponding to the position in the width direction of the film in the first inspection data in accordance with the input stretch angle and stretch rate, and applies these. As yet another example, when converting the second inspection data side, the comparison unit 513 can perform coordinate conversion using the same processing as when converting the first inspection data side, except for dividing by the stretch rate.

[0125] (S402) The comparison unit 513 generates a descriptor 2 for each feature point of the first and second test data. The comparison unit 513 uses, for example, a SIFT feature amount as the descriptor, or a probability density function of the feature points calculated by kernel density estimation as the descriptor.

[0126] (Steps S403 and S404) The comparison unit 513 compares the feature points of the first and second test data to search for the most similar points. The comparison unit 513 evaluates the similarity between the feature points using Descriptor 1 and Descriptor 2, and regards the most similar points as corresponding feature points.

[0127] For example, when comparing feature points between the first and second test data, the comparison unit 513 searches for feature points in the first test data that correspond to target feature points in the second test data. In this case, the comparison unit 513 determines that feature points in the first test data that match or have the closest intensity to the X and Y coordinates of descriptor 1 of the feature points in the second test data are the same point. Alternatively, the comparison unit 513 determines that feature points with the closest distance (Euclidean distance) between the X and Y coordinates of descriptor 1 are the same point (corresponding points). The comparison unit 513 excludes feature points that are farther apart than a set threshold from the determination of corresponding points. Note that, in this embodiment, the threshold value in the Y direction is set to a value that is two to three orders of magnitude larger than that in the X direction. For example, the threshold value in the X direction is several millimeters, and the threshold value in the Y direction is several meters. The reason why the threshold value in the Y direction is two to three orders of magnitude larger than that in the X direction is that the amount of change is greater.

[0128] The comparison unit 513 may also use descriptor 2 together with descriptor 1 to extract feature points that are most similar based on the distance between vectors in a high-dimensional vector space. In this case, the comparison unit 513 may use a probability density function calculated by kernel density estimation as described above as descriptor 2. Fig. 15 shows an example of a probability density function calculated by kernel density estimation, which indicates the position and intensity (density) of feature points. In Fig. 15, the vertical and horizontal axes represent X and Y coordinates, and it is shown that the higher the concentration, the higher the density.

[0129] The comparison unit 513 determines that one feature point corresponds to only one other feature point. For example, for a feature point in the second test data, the comparison unit 513 registers the feature point in the first test data whose descriptor vectors are closest to the feature point in the second test data as the corresponding point in the corresponding point list.

[0130] 16 is an example of a corresponding point list stored in the storage unit 52. The corresponding point list associates each feature point in the second inspection data with the most similar feature point in the first inspection data. The corresponding point list also includes the X and Y coordinates of the feature points in the second inspection data, the Euclidean distance between the associated feature points, the difference dx in the X coordinate, and the difference dy in the Y coordinate. A ratio may be used as the difference.

[0131] (Step S405) The analysis unit 514 generates correlation information between feature points that exist in both the first and second test data. That is, the analysis unit 514 generates one of the following four types of scatter plots as data indicating correlation information for feature points that have corresponding feature points in the corresponding point list. Furthermore, the analysis unit 514 may perform principal component analysis on the following four relationships to generate a scatter plot projected onto a coordinate system that maximizes the variance of the data: (1) X-coordinate on the horizontal axis and dx on the vertical axis (X-dx scatter plot), (2) X-coordinate on the horizontal axis and dy on the vertical axis (X-dy scatter plot), (3) Y-coordinate on the horizontal axis and dy on the vertical axis (Y-dy scatter plot), (4) Y-coordinate on the horizontal axis and dx on the vertical axis (Y-dx scatter plot).

[0132] FIG. 17A is an example of a scatter diagram corresponding to (1) above. FIG. 17B is an example of a scatter diagram corresponding to (2) above. FIG. 17C is an example of a scatter diagram corresponding to (3) above. FIG. 17D is an example of a scatter diagram corresponding to (4) above. FIG. 18 is another example of a scatter diagram corresponding to (1) above, illustrating bowing during the stretching process. In these figures, the horizontal axis indicates the X coordinate (or Y coordinate) of the feature point in the second inspection data. Furthermore, the analysis unit 514 may calculate statistical information (e.g., a regression equation, a correlation coefficient, etc.) as correlation information instead of or together with the scatter diagram. In FIGS. 17A-17D and 18, the regression equation of the scatter data is also shown. Furthermore, a histogram, Pareto chart, or bubble chart may be used instead of the scatter diagram.

[0133] (Step S36) The output unit 516 displays and outputs the correlation information or outputs an alert. For example, the output unit 516 displays and outputs the correlation information on the terminal device 70. The output unit 516 displays the correlation information on the operation screen of the terminal device 70. The output unit 516 may also notify the user of the alert by audio information such as an alarm sound or by tactile information such as vibrating the mobile terminal. FIG. 19 shows an example of an operation screen 702 for accepting correction amounts, which displays a scatter plot as correlation information. This operation screen 702 is displayed following the operation screen 701. For example, the scatter plot as correlation information generated in step S405 is displayed in the preview area b10 of the operation screen 702 shown in FIG. 19. Note that a correlation coefficient may be superimposed on the preview area b10. The user can determine whether the association is appropriate by referring to the correlation information displayed in the preview area b10 as shown in FIG. 19. By referring to a graph such as a scatter diagram, the user can determine whether the correspondence between the feature points of the two pieces of inspection data is satisfactory by reviewing the correction amount.

[0134] As a modified example, the display range may be set by the user as a longitudinal or lateral display range (preview X-axis), and the preview may be displayed within that range. In this case, the correction amount may be applied to a section of the display range rather than the entire range, or a section may be set separately, and the correction amount may be set individually for each section.

[0135] As another modification, only the correlation coefficient may be displayed, or statistical information such as the correlation coefficient may be displayed in a window in the preview area b10.

[0136] As a further modification, the following may be adopted. For example, when a correction amount is input and feature points recalculated based on this correction amount are displayed in the preview area b1, the plot (result data) before the correction amount is applied and the plot after the correction amount are applied may be displayed side by side or superimposed by using different colors. This allows the user to compare the result data before and after the correction and to understand the validity of the input correction amount.

[0137] (Step S37) If the user determines by looking at the scatter diagram that the correlation is poor, the user inputs a correction amount to see if it can be improved. In response to this, the control unit 51 advances the process to step S50 in response to the reception unit 512 receiving the correction amount from the user (YES).

[0138] The types of correction amounts accepted by the accepting unit 512 include the following. Note that inversion correction may also be included as a correction amount. Inversion correction is a correction in which the X coordinate or Y coordinate is inverted relative to a reference (the center of the width or the end of the length). (a) Tilt correction amount (rotation) (θ direction), (b) X coordinate correction amount (X direction), (c) Y coordinate correction amount (Y direction).

[0139] (a) By accepting the tilt correction amount, the coordinates of one of the two test data are transformed. This tilt correction amount corresponds to the expansion / contraction ratio. For example, in FIGS. 17 and 18, applying the tilt correction amount has the same effect as rotating the entire scatter plot. The input of (a) may also be accepted as (a11) an X correction amount at the X coordinate correction position or (a12) a Y correction amount at the Y coordinate correction position. For (b) the X coordinate correction amount, the comparison unit 513 shifts the entire X coordinate of one of the test data according to the input correction amount. For example, the comparison unit 513 shifts the X coordinate of the first test data according to the input correction amount. In this case, in FIG. 18, the same effect occurs as if the entire plot of the scatter plot were shifted up or down. The same applies to (c) the Y coordinate correction amount. In this case, the entire Y coordinate of one of the test data is shifted according to the input correction amount. For example, in the example of FIG. 17, the entire data is shifted up or down according to the input Y coordinate correction amount.

[0140] The input example shown in FIG. 19 is an example of (a12). The user selects the Y-dy scatter plot with button b11 on the operation screen 702 in FIG. 19, and in response to the selection, a Y-dy scatter plot like the one shown in FIG. 17 is displayed in the preview area b10. The user enters -6.0 m in the input area b12 and 0 m in b13. By operating the recalculation button b14, recalculation is performed according to this input correction amount, and the display in the preview area b10 is updated (redisplayed). In this case, the center of the regression equation is fixed, and the leftmost side (b13: Y = 0 m) moves by -6.0 m. In other words, the entire coordinate system rotates counterclockwise so that the left end of the regression equation moves down by 6.0 m.

[0141] (Step S50) FIG. 20 is a subroutine flowchart showing the comparison process 2 in step S50.

[0142] (Step S501) The comparison unit 513 moves the position of one of the feature points of the first and second test data in accordance with the correction amount (hereinafter referred to as the input correction amount) received in step S37. That is, the comparison unit 513 converts the coordinate system. In the following description, the comparison unit 513 is assumed to move the feature point of the first test data in accordance with the input correction amount.

[0143] For example, in the input example of FIG. 19 , the comparison unit 513 shifts the Y coordinate of the feature point whose Y coordinate is at the origin (0 m) using an input correction amount (-6.0 m). For Y coordinates other than the origin, the comparison unit 513 shifts the Y coordinate of the feature point by a value obtained by multiplying the input correction amount (-6.0 m) by the ratio of the distance to the center position ((yc-y) / yc). Here, yc is the coordinate of the center position. yc is half the value of the distance from the origin to the end of the data. The end is the last Y coordinate data of the first inspection data, which corresponds to the length of the film in the roll (the size of table T2 in FIG. 7 ). FIG. 21 shows an example in which a correction amount is applied. The same applies to the X coordinate; the coordinate of the feature point is shifted according to the user's input correction amount. In other words, by shifting the coordinate of the feature point through these processes, the entire system rotates counterclockwise (see arrow) around the axis of rotation on the regression equation, as shown in FIG. 21 .

[0144] (Steps S502 to S505) The processing here is the same as steps S402 to S405 in FIG. 14. The comparison unit 513 generates new feature point descriptor information using the coordinates converted in step S501, performs a matching process between feature points, associates corresponding feature points, and stores the associated feature points in a corresponding point list. The analysis unit 514 references the updated corresponding point list and generates correlation information between feature points present in both the first and second test data. The correlation information includes at least one of a scatter plot and statistical information, as described above. This completes the processing in FIG. 20, and the processing returns to the processing in FIG. 11. For example, a scatter plot like the one in FIG. 21 is displayed in the preview area b10 of the operation screen 702 in FIG. 19.

[0145] (Step S51) The output unit 516 again displays the relevance information. The processing here is the same as that in step S36. For example, the preview area b10 in FIG. 19 is the feature point after the coordinates have been moved in accordance with the received correction amount, and the generated relevance information is displayed in the preview area b10.

[0146] (Step S37: NO) When the user determines that the correlation is correct to a certain extent by referring to the correlation information such as a scatter diagram, or when the user determines that correction (re-correction) of the correction amount is unnecessary (NO), the user presses the register button b16 on the operation screen 701. In response to the operation of the register button b16, the control unit 51 advances the process to step S38.

[0147] (Step S38) FIG. 22 shows an example of feature point extraction conditions that have been confirmed and recorded in the inspection DB of the storage unit 52. The control unit 51 records the expansion / contraction ratios and correction amounts received in steps S34 and S37, linking them to the lot and the combination of the first and second inspection data. Thereafter, when using film rolls of the same type as the lot, reading out these feature point extraction conditions can eliminate the need for adjustments, and by comparing with the previous lot under the same conditions, differences between lots can be identified. Note that feature point extraction may be performed and recorded using intermediate correction amounts before confirmation. For example, feature points may be extracted (classified) according to the correction amounts each time a correction amount is input.

[0148] Furthermore, the extraction unit 515 classifies third-type feature points, which are associated with each other in the first and second inspection data, into two types: a third-type feature point of rank A and a third-type feature point of rank B, based on their distance from the regression equation. FIG. 23 is a schematic diagram illustrating classification based on distance from the regression equation. The extraction unit 515 classifies feature points whose distance from the regression equation is equal to or less than a predetermined threshold into a third-type feature point a, and those whose distance exceeds the predetermined threshold into a third-type feature point b. This classification is performed using the Y-dy scatter diagram (3) described above, but other scatter diagrams (e.g., X-dx) may also be used. Furthermore, classification may be performed based on both the distance from the regression equation of the Y-dy scatter diagram and the distance from the regression equation of the X-dx scatter diagram, and the two may be compared and presented. For example, if both are classified as rank A, the feature points are classified as A1 (S rank), and if only one of them is classified as rank A, the feature points are classified as A2.

[0149] The distance between the feature point and the regression equation is measured using the distance on the vertical axis (dy), but may also be measured using Euclidean distance. The predetermined threshold value is a preset value, but may also be set using statistical information such as standard deviation (σ). The extraction unit 515 classifies feature points that fall within a range of +1σ to -1σ from the regression equation into a third type a, and other feature points into a third type b. The extraction unit 515 may record the separation of the third types a and b in a corresponding point list. Feature points classified into the third type a with rank A have a higher degree of reliability that they are the same feature point.

[0150] (Step S39) The extraction unit 515 classifies feature points from the correspondence list, the first test data, and the second test data. Specifically, the extraction unit 515 classifies, in the correspondence list, feature points of the second test data that are not associated with feature points of the first test data as second-type feature points. Furthermore, the extraction unit 515 classifies, in the correspondence list, feature points of the first test data that are not included in the correspondence list (feature points that are not associated with feature points of the second test data) as first-type feature points (see Table T5 in FIGS. 5 and 8 ).

[0151] (Step S40) The output unit 516 registers the extraction result (extraction data) generated in step S38 in the test data DB, and transmits the extraction result to the terminal device 70. This completes the feature point extraction process shown in FIG. 11 (END).

[0152] As described above, the information processing system according to this embodiment includes a comparison unit that compares first feature point information of a web in the first inspection data with second feature point information of a web in the second inspection data and extracts identical feature points in the first and second inspection data. The information processing system also includes an analysis unit that generates relationship information indicating the relationship between the coordinate difference between the first inspection data and the second inspection data for each of the feature points extracted by the comparison unit and the coordinate position on the entire web, and an output unit that outputs the relationship information. This allows for efficient collection of information useful for process improvement and shipping standard setting both during the production of film rolls or webs and during post-processing processes using such film rolls. In particular, by checking the displayed relationship information, the user can determine whether the feature points in the first and second inspection data are correctly matched. Furthermore, by accepting a correction amount input by the user, more accurate feature point matching (third-type feature points) can be achieved, which ultimately allows for more accurate classification of the first, second, and third-type feature points.

[0153] Second Embodiment In the second embodiment, an alert is issued in accordance with a correlation coefficient in a scatter diagram. Fig. 24 is a flowchart showing the process of extracting feature points in the second embodiment.

[0154] In Fig. 24, steps S71 to S76 and S77 to S91 correspond to steps S31 to S36 and S37 to S51, respectively, in the first embodiment shown in Fig. 12. In the second embodiment, step S765 is carried out.

[0155] (Step S765) The analysis unit 514 calculates the correlation coefficient, and issues an alert if the correlation coefficient is equal to or less than a first predetermined threshold. For example, if the absolute value of the correlation coefficient is 0.5 or less, an alert is displayed on the terminal device 70. Alternatively, if the regression equation is a regression line and its slope is close to zero (i.e., flat), the analysis unit 514 calculates the variance of the difference values ​​(dy or dx) of the feature points, and if the variance is equal to or greater than a second threshold, an alert is displayed.

[0156] FIG. 25 shows examples of distribution diagrams and alert displays. FIG. 25(A) shows a case where the correlation coefficient is high or the variance of the difference dy is small, indicating normality. On the other hand, FIGS. 25(b) and 25(c) show a case where the correlation coefficient is low or the variance of the difference dy is large, indicating abnormality. In such cases, the output unit 516 displays an alert on the display unit of the terminal device 70. This allows the user to understand that some kind of problem has occurred.

[0157] The configuration of the information processing system 50 described above is a main configuration used to explain the features of the above embodiment. However, the present invention is not limited to the above configuration and may be modified in various ways within the scope of the claims. Furthermore, configurations that are included in general information processing devices / systems are not excluded. For example, in this embodiment, a stretching process is assumed to exist between the positions where the first test data and the second test data are collected. While FIGS. 11 and 12 show an example in which an expansion / contraction ratio is accepted, the process of accepting the expansion / contraction ratio (step S34) may be omitted. For example, if there is no stretching process between the first and second test data, the process of accepting the expansion / contraction ratio is omitted. In this case, the comparison unit 513 performs the comparison process at step S35 using a fixed expansion / contraction ratio.

[0158] Furthermore, when a lot is selected, if there is a track record of producing products under the same production conditions in the past and the correction amounts, etc. set and confirmed by the user are recorded as feature point extraction conditions (see FIG. 22), the correction amounts, etc. applied to the same product in the past may be read out and presented to the user. This reduces the number of trial and error steps required by the user, making it easier to set appropriate correction amounts.

[0159] Furthermore, for example, the information processing system 50 may include an inspection device 90 disposed in the first manufacturing process and / or the second manufacturing process. The feature point generation function of the image analysis unit 93 of the inspection device 90 may be performed by the control unit 51 of the information processing system 50. In this case, the inspection device 90 sends image data of an image of the film surface and the image capture conditions (information such as transport speed, camera orientation, and angle of view) to the information processing system 50, and the feature point generation process is performed on the control unit 51 side.

[0160] Furthermore, the means and methods for performing various processes in the information processing system 50 according to the above-described embodiment can be realized by either a dedicated hardware circuit or a programmed computer. The program may be provided, for example, by a computer-readable recording medium such as a USB memory or a DVD (Digital Versatile Disc)-ROM, or may be provided online via a network such as the Internet. In this case, the program recorded on the computer-readable recording medium is typically transferred and stored in a storage unit such as a hard disk. The program may also be provided as standalone application software, or may be incorporated into the software of a device as a function of the device.

[0161] While embodiments of the present invention have been described and illustrated in detail, the disclosed embodiments are made for purposes of illustration and example only and are not intended to be limiting, and the scope of the present invention should be construed by the language of the appended claims.

[0162] This application is based on a Japanese patent application (Patent Application No. 2024-056247) filed on March 29, 2024, the disclosure of which is incorporated herein by reference in its entirety.

[0163] 50 Information processing system 51 Control unit 511 Acquisition unit 512 Reception unit 513 Comparison unit 514 Analysis unit 515 Extraction unit 516 Output unit 52 Storage unit 90 Inspection device 1000 Film roll manufacturing device 2000 Product manufacturing device

Claims

1. An information processing system comprising: an acquisition unit that acquires first inspection data from a first manufacturing process in which a web is manufactured or a manufactured web is post-processed, and second inspection data from a second manufacturing process in which post-processing using the web is performed after the first manufacturing process; a comparison unit that compares first feature point information of the web in the first inspection data with second feature point information of the web in the second inspection data, and extracts identical feature points in the first and second inspection data; an analysis unit that generates relationship information indicating the relationship between the coordinate difference values ​​in the first inspection data and the second inspection data for each of the multiple feature points extracted by the comparison unit and the coordinate position on the entire web; and an output unit that outputs the relationship information.

2. The information processing system according to claim 1, wherein the relationship information is a graph showing the relationship between coordinate difference values ​​and overall coordinate positions.

3. An information processing system according to claim 1 or claim 2, wherein the relationship information is statistical information indicating the relationship between the coordinate difference value and the overall coordinate position.

4. An information processing system as described in claim 1, further comprising a receiving unit that receives a correction amount for the coordinates of the first inspection data and / or the second inspection data, wherein the comparing unit corrects the coordinates of the feature points with the correction amount received by the receiving unit, then compares the first feature point information of the web in the first inspection data with the second feature point information of the web in the second inspection data, and extracts identical feature points in the first and second inspection data.

5. The information processing system of claim 4, wherein the reception unit receives the correction amount after the output unit displays the relationship information, and in response to the reception unit receiving the correction amount, the comparison unit again extracts the same feature points, the analysis unit generates the relationship information, and the output unit again displays the relationship information.

6. The information processing system of claim 1, wherein the relationship information is a scatter plot and a regression equation that represent the relationship between coordinate difference values ​​and overall coordinate positions, and further comprises an extraction unit that classifies the feature points according to the distance from the feature points in the scatter plot to the regression equation.

7. The information processing system of claim 1, wherein the relationship information includes a correlation coefficient indicating the relationship between a coordinate difference value and an overall coordinate position, or a variance of the difference value, and the analysis unit generates an alert when the absolute value of the correlation coefficient is equal to or less than a first predetermined threshold value, or when the variance is equal to or greater than a second predetermined threshold value, and the output unit issues an alert.

8. A method for extracting feature points of a web, comprising: (a) acquiring first inspection data in a first manufacturing process in which a web is manufactured or a manufactured web is post-processed; (b) acquiring second inspection data in a second manufacturing process in which post-processing using the web is performed after the first manufacturing process; (c) comparing first feature point information of the web in the first inspection data with second feature point information of the web in the second inspection data; (d) extracting identical feature points in the first and second inspection data based on the comparison result of step (c); (e) generating relationship information indicating the relationship between the difference in coordinates between the first inspection data and the second inspection data for each of the multiple feature points extracted in step (d) and the coordinate position on the entire web; and (f) outputting the relationship information generated in step (e).

9. The feature point extraction method according to claim 8, wherein the relationship information is a graph showing the relationship between coordinate difference values ​​and overall coordinate positions.

10. A control program for causing a computer to execute the extraction method according to claim 8 or claim 9.

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