Feature point extraction method, control program, and information processing system

Abstract

This method for extracting a feature point of a web comprises: a step (c) for receiving an input of an expansion / contraction rate of a web generated between a first manufacturing step and a second manufacturing step; a step (d) for comparing first feature point information of the web in first inspection data and second feature point information of the web in second inspection data, by using the received expansion / contraction rate; and a step (e) for extracting a feature point which exists in one of the first or second inspection data but does not exist in the other inspection data, or, is determined to be a defect in the one inspection data and is determined not to be a defect in the other inspection data, on the basis of the comparison results from step (d).

Description

Feature point extraction method, control program, and information processing system

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

[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 occurred during a post-processing step, and in doing so, it is necessary to match the coordinate system on the web in the previous process with the coordinate system in the subsequent process. Webs can be processed through stretching processes such as uniaxial stretching and biaxial stretching. In these stretching processes, depending on the set conditions, the length of the web in the longitudinal direction (conveyance direction) and transverse direction (width direction) can increase by several tens of percent to several hundred percent (hereinafter referred to as the expansion / contraction rate).

[0005] When such a stretching step is included in the subsequent process, it is necessary to know the expansion / contraction ratio when adjusting the coordinate systems on the web surface in the previous process and the subsequent process.

[0006] The following Patent Document 1 addresses the issue of suppressing degradation of print quality in an inkjet printing device due to expansion and contraction of a substrate, such as printing paper or a resin film, that occurs during the ink absorption and drying process when printing on the substrate. This printing device prints image data in which marks are arranged in advance. An estimation model is then trained by machine learning using the mark positions and image data as training data. By inputting submitted data into this estimation model, an estimation result indicating the expansion and contraction state of the substrate due to ink before printing is output.

[0007] Japanese Patent Application Laid-Open No. 2022-110632

[0008] The technology of Patent Document 1 involves printing image data in which learning marks are arranged, and learning an estimation model based on the measurement positions of the printed marks. It is necessary to prepare an estimation model according to the substrate.

[0009] The present invention has been made in consideration of the above circumstances, and aims to efficiently collect information that takes into account the stretch state and is useful for process improvement and setting shipping standards both when manufacturing a web and in the manufacturing process where post-processing is performed using the web.

[0010] The above object of the present invention can be achieved by the following means.

[0011] (1) 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) accepting input of a rate of expansion and contraction of the web occurring from the first manufacturing process to the second manufacturing process; (d) 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 using the accepted rate of expansion and contraction; and (e) extracting feature points that exist in both the first and second inspection data, or feature points that exist in one of the first and second inspection data but not in the other, based on the comparison result of step (d).

[0012] (2) The feature point extraction method according to (1) above, wherein in the step (e), feature points present in both the first inspection data and the second inspection data are extracted.

[0013] (3) The method for extracting feature points described in (1) above, wherein the first inspection data and the second inspection data are inspection data obtained by processing images or signals of the web to extract feature point information, and the feature point information includes information on the positions of feature points on the web, and the step (d) includes a step (d1) of aligning the first inspection data with the web in the second inspection data, and the step (d1) includes a process of moving the position of one of the feature points in the first inspection data and the second inspection data using the expansion / contraction ratio.

[0014] (4) A method for extracting feature points described in (1) above, wherein the expansion rate received in step (c) is the expansion rate in the width direction, the length direction, and / or the thickness direction of the web.

[0015] (5) The feature point extraction method according to (3) above, wherein the first inspection data and the second inspection data are inspection data obtained by processing images or signals of the web to extract feature point information, the feature point information including information on the size of the feature points and their positions on the web, and the step (d) includes a step (d1) of aligning the first inspection data with the web in the second inspection data, and the step (d1) includes a process of moving the position of one of the feature points in the first inspection data and the second inspection data in the width direction and / or the length direction using the expansion rate in the width direction and / or the expansion rate in the length direction.

[0016] (6) The feature point extraction method according to (2) above, further comprising: a step (f) of calculating a degree of deviation between the positions of feature points present in both the first inspection data and the second inspection data extracted in the step (e); and a step (g) of outputting the calculated degree of deviation.

[0017] (7) The method for extracting feature points according to (1) above, wherein the expansion / contraction ratio received in step (c) is the expansion / contraction ratio for each of a plurality of stages obtained by dividing the width direction of the web into stages.

[0018] (8) A control program for causing a computer to execute the extraction method according to any one of (1) to (7) above.

[0019] (9) An information processing system having: 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 reception unit that receives input of a web expansion rate occurring from the first manufacturing process to the second 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 using the received expansion rate; and an extraction unit that extracts feature points that exist in both the first and second inspection data, or feature points that exist in one of the first and second inspection data but not in the other inspection data, based on the comparison result of the comparison unit.

[0020] The feature extraction method of the present invention includes a step (c) of comparing first feature information of the film in the first inspection data from the first manufacturing process with second feature information of the film in the second inspection data from the second manufacturing process, and a step (d) of extracting, based on the comparison result of step (c), feature points that are present in one of the first and second inspection data but not in the other, or feature points that are determined to be defects in one of the inspection data but not in the other, thereby making it possible to efficiently collect information useful for process improvement and setting shipping standards both during film manufacturing and in manufacturing processes where post-processing is performed using the film.

[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 the comparison process 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; an example of a list of corresponding points; an example of a display of a distribution map as a deviation; an example of a display of a distribution map as a deviation; and an example of an operation screen in a modified example.

[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 film F8 is the Y direction, and the direction perpendicular to the conveying direction, the width direction of film F8, is the X direction. The Y direction or conveying direction is also referred to as MD (Machine Direction). The X direction or 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] While this stretching step illustrates an example of sequential stretching in which the MD stretching step is followed by the TD stretching step, the present invention is not limited to this and may also employ a simultaneous biaxial method in which MD stretching and TD stretching are performed simultaneously. An oblique stretching step other than the TD stretching step may also be employed. The TD stretching step involves stretching in a direction parallel to the width direction of the film. 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 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 continuous still images. Furthermore, feature points may be extracted directly from signal data without converting the data into image data. The number of cameras 92, the angle of view, and the distance to the film surface 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 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 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 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 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) linked to 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 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 third type feature points, and then first and second type feature points may be extracted accordingly.

[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 an input of an expansion / contraction ratio from a user. The comparison unit 513 extracts feature points from each of the first and second inspection data and performs a comparison process using the received expansion / contraction ratio. The comparison unit 513 searches for corresponding feature points between the first and second inspection data through the comparison process. In the comparison process, the comparison unit 513 generates feature point descriptors (descriptor 2, described below) for the two pieces of inspection data (image data), performs a feature point matching process between the inspection data using the feature point descriptors, and outputs the comparison result (a corresponding point list shown in FIG. 16, described below). The analysis unit 514 calculates a deviation index using the corresponding point list. The deviation index includes statistical information such as a scatter plot and a correlation coefficient. The 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 size (diameter, area) of the feature point. 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 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 Figure 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 the classifications shown in Figure 5 above. The integrated feature point IDs are automatically assigned consecutive numbers, and integrated feature points are generated corresponding to feature points that are 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.

[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 b6 and b7 in FIG. 12 , which will be described later).

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

[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 analysis unit 93 performs image processing described below on the image data to generate a plurality of feature points.

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

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

[0096] The analysis unit 93 divides the image data into a plurality of regions. For example, the 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 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, 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 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 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 analysis unit 93 performs the same process on areas other than the area a1.

[0107] After processing each of the regions a1 to an, the analysis unit 93 integrates the results for each of the regions a1 to an, and data processing ends. Specifically, the 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 analysis unit 93 stores the results of the data processing in the storage unit 94. The 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 analysis unit 93 stores the generated inspection data including feature point information on 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 b6 and b7. 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. Note that a branch number 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 number of the lot ID or a new lot ID is assigned in the subsequent process. Conversely, two or three film rolls may be spliced ​​together 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). Also, 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 first inspection data) depending on information indicating whether the shooting area of ​​the camera 92 is set to the front or back side of the film F8.

[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 reception unit 512 receives the expansion / contraction ratio from the user. For example, the expansion / contraction ratio is input via an operation screen 701 displayed on the terminal device 70, as shown in FIG. 12. The user can enter any value within a predetermined range (e.g., 50 to 300%) using buttons b1 and b2 on the numeric keypad. The reception unit 512 receives the expansion / contraction ratio in the Y direction (longitudinal direction) via button b1. The reception unit 512 also receives the expansion / contraction ratio in the X direction (transverse direction) via button b2. The operation screen 701 in FIG. 12 shows the state in which 140% has been entered. A value greater than 100% indicates that the film in the second inspection data has stretched more than the film in the first inspection data. The user can set the expansion / contraction ratio based on the condition settings for post-processing (second manufacturing process). These condition settings are described in Table T2 related to the lot list and can be referenced by the user. For example, if the film F8 expands or contracts due to the settings of the heating temperature and tension in post-processing in the second manufacturing step, and if the expansion / contraction rate can be estimated in advance, the user inputs the expansion / contraction rate.

[0122] In addition, FIG. 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 accepts expansion / contraction ratios for each of the X and Y directions. This is not limiting. For example, if the stretching unit 03 performs an oblique stretching process, the accepting unit 512 may accept the stretching ratio (expansion / contraction ratio) for the oblique stretching. For example, if the film F8 is intended for use as a retardation film, the oblique stretching process is performed. In this case, the accepting unit 512 accepts input of a stretching angle value within a predetermined range (40 to 50° or 130 to 140°). Alternatively, the degree of shear deformation may be accepted instead of this stretching angle. For example, the accepting unit 512 accepts the web orientation angle and stretching ratio in the orientation angle direction calculated from the bending angle during stretching and the MD and TD magnifications.

[0123] (Step S35) The comparison unit 513 searches for feature points in one test data that are identical to or correspond to feature points in the other test data through a comparison process, and matches the feature points with each other. Fig. 14 is a subroutine flowchart showing the process 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 (expansion rate) in the X direction and the stretch rate (expansion 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. Furthermore, as another example described above, when the orientation angle of the web and the stretch rate in the orientation angle direction are received, the calculated stretch rates in the X direction and the Y direction are calculated and applied. As yet another example, when converting the second inspection data, the comparison unit 513 can perform coordinate conversion using the same process as when converting the first inspection data, 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 inspection data to search for the most similar points. The similarity between the feature points is evaluated using Descriptor 1 and Descriptor 2, and the most similar points are regarded 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 in the Y direction is set to a value that is two to three orders of magnitude larger than the threshold in the X direction. For example, the threshold in the X direction is several millimeters, and the threshold in the Y direction is several meters.

[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, a probability density function calculated by kernel density estimation as described above may be used 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 density, 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 describes 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.

[0131] (Step S405) The analysis unit 514 generates the degree of discrepancy 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 the degree of discrepancy for feature points that have corresponding feature points in the corresponding point list: (1) horizontal axis: X coordinate, vertical axis: dx, (2) horizontal axis: X coordinate, vertical axis: dy, (3) horizontal axis: Y coordinate, vertical axis: dy, (4) horizontal axis: Y coordinate, vertical axis: dx.

[0132] FIG. 17 is an example of a scatter diagram corresponding to (3) above. FIG. 18 is an example of a scatter diagram corresponding to (1) above. The horizontal axis indicates the Y coordinate (or X coordinate) of the feature point in the second test data. The analysis unit 514 may also calculate statistical information (e.g., a regression line, a correlation coefficient, etc.) as the deviation instead of or together with the scatter diagram. In FIGS. 18 and 19, the regression line of the scatter data is also shown.

[0133] (Step S36) The output unit 516 outputs the deviation. For example, the scatter plot representing the deviation generated in step S405 is displayed in the preview area b5 of the operation screen 701 shown in Fig. 12. Note that the correlation coefficient may be displayed superimposed in the preview area b5. By referring to the deviation displayed in the preview area b5 as shown in Fig. 12, the user can determine whether the entered expansion / contraction ratio was appropriate.

[0134] (Step S37) If the user recognizes that the expansion / contraction ratio needs to be corrected (YES), the user inputs the corrected expansion / contraction ratio on the step operation screen 701. In response to receiving the new expansion / contraction ratio in step S34, the control unit 51 repeats the processing from step S34 onwards.

[0135] On the other hand, if the user determines that the expansion / contraction ratio does not need to be corrected (NO), the user presses the register button b4 on the operation screen 701. In response to the operation of the register button b4, the control unit 51 advances the process to step S38.

[0136] (Step S38) 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 the feature points that are associated in the correspondence list as third-type feature points. Furthermore, the extraction unit 515 classifies the feature points of the second test data that are not associated with feature points of the first test data in the correspondence list as second-type feature points. Furthermore, the extraction unit 515 classifies the 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 ).

[0137] (Step S39) 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).

[0138] As described above, in this embodiment, the system accepts input of the web expansion rate and uses the accepted expansion rate to compare first feature point information of the film in the first inspection data with second feature point information of the film in the second inspection data. Based on the comparison results, feature points that are present in one of the first and second inspection data but not in the other, or feature points that are determined to be defective in one inspection data but not in the other, are extracted. This allows for efficient collection of information useful for process improvement and setting shipping standards both when producing film for film rolls and in the manufacturing process where post-processing is performed using the film. In particular, when a stretching process is included between the first and second manufacturing processes, using the input stretch rate allows for accurate feature point comparison and, ultimately, accurate feature point extraction.

[0139] (Variation 1) In the above embodiment, an example was shown in which one value was set as the stretching ratio in each of the X and Y directions, but it may also be possible to divide it into multiple stages as shown below and accept an expansion / contraction ratio for each stage.

[0140] FIG. 19 shows an operation screen 702 displayed on the terminal device 70 in a modified example. On the operation screen 702, the user can use button b20 to divide the X direction (width direction) into five equal sections and input an individual stretch rate for each section. Similarly, the user can use button b10 to divide the Y direction (length direction) into five equal sections and input an individual stretch rate for each section. In the stretching process, the film is stretched by heating and stretching. However, if the heating is uneven and there is a temperature distribution due to the process configuration, the stretch rate will vary depending on the position on the web surface. For example, this may occur when the heating temperature is different at the center and the edges in the width direction. In this modified example, in step S34, the accepting unit 512 accepts input of a finer stretch rate depending on the position in the width direction. Then, in step S401, the comparing unit 513 divides the X coordinate of each feature point in the first inspection data into sections based on the center point and converts it into a value multiplied by the stretch rate set for each section. The reception unit 512 and the comparison unit 513 can perform similar processing in the longitudinal direction.

[0141] In this way, in the modified example, by accepting the expansion / contraction ratio according to the division in the width direction, it is possible to more accurately compare feature points and, in turn, to more accurately extract feature points.

[0142] The configuration of the information processing system 50 described above is a description of the main configuration in explaining the features of the above embodiment, but is not limited to the above configuration and can 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, the following modification 2 and the following modifications can be applied.

[0143] (Variation 2) For example, in the examples shown in Figures 12 and 19, the expansion / contraction ratio can be set in both the X and Y directions, but it is also possible to set only one of them. It is also possible to set the expansion / contraction ratio in the thickness direction. In this case, the expansion / contraction ratio is converted to the same expansion / contraction ratio for the entire X and Y directions depending on the input setting of the expansion / contraction ratio in the thickness direction. For example, if the expansion / contraction ratio in the thickness direction is 50%, the area will be approximately 200%, and the expansion / contraction ratio in X and Y will be 1 / 2 power, or 144%.

[0144] (Variation 3) When a lot is selected, if there is a history of producing products under the same production conditions in the past and the expansion / contraction ratio set and confirmed by the user is recorded, the expansion / contraction ratio 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 an appropriate expansion / contraction ratio. This allows for correction of any deviations in coordinate settings in the inspection device when using the same inspection device 90 as in the past between lots.

[0145] (Variation 4) In the example shown in Fig. 19, the longitudinal position is divided into multiple stages and the longitudinal expansion / contraction ratio can be set for each stage. However, the widthwise expansion / contraction ratio may also be set for each longitudinal section. Similarly, when the widthwise direction is divided into multiple stages, the longitudinal expansion / contraction ratio may also be set for each widthwise section. In this way, for example, bowing, which occurs when the longitudinal and / or widthwise expansion / contraction ratios differ depending on the widthwise position during film stretching, can be corrected.

[0146] (Variation 5) The expansion / contraction ratio may be estimated from the degree of deformation of the feature points and presented to the user as a recommended value. For example, this may be presented as shown in FIG. 12 or presented as an initial value to be initially displayed on buttons b1 and b2.

[0147] (Variation 6) 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. Furthermore, the feature point generation function of the 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 the 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.

[0148] 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.

[0149] 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.

[0150] This application is based on a Japanese patent application (Patent Application No. 2024-056234) filed on March 29, 2024, the disclosure of which is incorporated herein by reference in its entirety.

[0151] 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. 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, which is performed after the first manufacturing process; (c) accepting input of the expansion / contraction rate of the web occurring from the first manufacturing process to the second manufacturing process; (d) 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 using the accepted expansion / contraction rate; and (e) extracting feature points that are present in both the first and second inspection data, or feature points that are present in one of the first and second inspection data but not in the other, based on the comparison result of step (d).

2. The feature point extraction method according to claim 1, wherein in step (e), feature points present in both the first inspection data and the second inspection data are extracted.

3. The method for extracting feature points according to claim 1, wherein the first inspection data and the second inspection data are inspection data obtained by processing images or signals of the web to extract feature point information, and the feature point information includes information on the positions of feature points on the web, and step (d) includes step (d1) of aligning the first inspection data with the web in the second inspection data, and step (d1) includes processing of moving the positions of feature points in one of the first inspection data and the second inspection data using the expansion / contraction ratio.

4. A feature point extraction method according to claim 1, wherein the expansion rate received in step (c) is the expansion rate in the width direction, the length direction, and / or the thickness direction of the web.

5. The feature point extraction method according to claim 3, wherein the first inspection data and the second inspection data are inspection data obtained by processing images or signals of the web to extract feature point information, the feature point information including information on the size of the feature points and their positions on the web, and step (d) includes step (d1) of aligning the first inspection data with the web in the second inspection data, and step (d1) includes processing of moving the position of one of the feature points in the first inspection data and the second inspection data in the width direction and / or the length direction using the expansion rate in the width direction and / or the expansion rate in the length direction.

6. The feature point extraction method according to claim 2, further comprising: a step (f) of calculating a degree of deviation between the positions of feature points present in both the first inspection data and the second inspection data extracted in step (e); and a step (g) of outputting the calculated degree of deviation.

7. The feature point extraction method according to claim 1, wherein the expansion / contraction ratio received in step (c) is the expansion / contraction ratio for each of a plurality of stages obtained by dividing the width direction of the web into stages.

8. A control program for causing a computer to execute the extraction method according to any one of claims 1 to 7.

9. 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 reception unit that receives input of the expansion rate of the web occurring from the first manufacturing process to the second 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 using the received expansion rate; and an extraction unit that extracts feature points that exist in both the first and second inspection data, or feature points that exist in one of the first and second inspection data but not in the other, based on the comparison result of the comparison unit.

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