Inspection device, inspection method, and program

Abstract

To assess the quality of an inspection object with high accuracy, even when image resolutions are insufficient.SOLUTION: A first position determination unit 120 generates statistical data (first data) of pixel values in the inside of a first frame at each position while moving the first frame in a region of image that includes an inspection object. Then, the first position determination unit 120 determines the position of the first frame using this first data. A second position determination unit 130 moves a second frame, which is smaller than the first frame, inside of the first frame and generates statistical data (second data) of pixel values in the second frame at each position. Then, the second position determination unit 130 determines the position of the second frame using the second data. An assessment unit 140 assesses the presence of abnormality in the inspection object using data (third data) that pertains to pixel values in the first frame and data (fourth data) that pertains to pixel values in the second frame.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to an inspection device, an inspection method, and a program. [Background technology]

[0002] In recent years, the quality of an inspection object has been determined by processing image data obtained by photographing the inspection object.

[0003] For example, Patent Document 1 discloses a technique for accurately inspecting defects such as density defects and printing defects even when a printed matter expands or contracts during the manufacturing process. Specifically, a matching image is created by pattern matching between an inspection target image acquired by capturing an image of the printed matter to be inspected and a position reference image. The reference position image is an image to which reference coordinates are assigned as a reference position when determining whether the printed matter is good or bad. Then, a level correction image is created by correcting the density of the base material in the matching image to match the reference density that is the reference when determining whether the printed matter is good or bad. Next, an upper threshold image and a lower threshold image that are at least the upper limit or lower limit of position variation within the acceptable range when determining whether the printed matter is good or bad are created. Next, the level correction image is compared with the upper and lower threshold images, respectively, and abnormal pixels that exceed the threshold value of the upper or lower threshold image are counted within a determination area of ​​any size of the level correction image, to determine whether the printed matter is good or bad.

[0004] Patent Document 2 discloses the following technology. First, the printed surface of the printed matter is optically scanned to extract density signals, and the density signals are sampled to extract a desired number of density sample data. Next, from the density sample data, an appropriate number of data items are extracted in sequence starting from the highest density and an appropriate number of data items are extracted in sequence starting from the lowest density. Then, for each of these appropriate numbers of data items, the average value of the high density data and the average value of the low density data are calculated. Then, the difference between these two average values ​​is calculated, and this difference is compared with a predetermined value. If the result of this comparison is outside a predetermined range, it is determined that the density is poor. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2014-38425 A [Patent Document 2] Japanese Patent Application Publication No. 05-185574 Summary of the Invention [Problem to be solved by the invention]

[0006] When image data is used to determine the quality of an object to be inspected, for example, when high-speed processing is required, sufficient resolution may not be obtained. One of the objects of the present invention is to determine the quality of an object to be inspected with high accuracy even in such cases. [Means for solving the problem]

[0007] According to the present invention, there is provided an image acquisition means for acquiring an image including an inspection object; a first position determination means for generating first data, which is statistical data of pixel values ​​within a first frame while moving the first frame in a region of the image including the inspection object, and determining a position of the first frame using the first data; a second position determination means for generating second data, which is statistical data of pixel values ​​within the second frame, while moving a second frame smaller than the first frame within the first frame, and determining a position of the second frame using the second data; a determination means for determining the presence or absence of an abnormality in the inspection object by using third data on the pixel values ​​in the first frame and fourth data on the pixel values ​​in the second frame; An inspection apparatus is provided comprising:

[0008] According to the present invention, a computer An image acquisition process for acquiring an image including an object to be inspected; a first position determination process for generating first data, which is statistical data of pixel values ​​within a first frame while moving the first frame in a region of the image including the inspection object, and determining a position of the first frame using the first data; a second position determination process for generating second data, which is statistical data of pixel values ​​within the second frame, while moving a second frame smaller than the first frame within the first frame, and determining a position of the second frame using the second data; a determination process for determining the presence or absence of an abnormality in the inspection object by using third data on the pixel values ​​in the first frame and fourth data on the pixel values ​​in the second frame; An inspection method is provided for carrying out the above.

[0009] According to the present invention, a computer includes: an image acquisition function for acquiring an image including an object to be inspected; a first position determination function that generates first data, which is statistical data of pixel values ​​within a first frame, while moving the first frame in a region of the image that includes the inspection object, and determines a position of the first frame using the first data; a second position determination function that generates second data, which is statistical data of pixel values ​​within the second frame, while moving a second frame smaller than the first frame within the first frame, and determines a position of the second frame using the second data; a determination function for determining the presence or absence of an abnormality in the inspection object by using third data on the pixel values ​​in the first frame and fourth data on the pixel values ​​in the second frame; A program will be provided to help students develop these skills. Effect of the Invention

[0010] According to the present invention, even when the image resolution is insufficient, the quality of the inspection object can be determined with high accuracy. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a diagram for explaining a usage environment of an inspection device according to an embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of a functional configuration of an inspection apparatus. [Diagram 3] FIG. 2 is a diagram illustrating an example of an image generated by an imaging device. [Figure 4] 11 is a diagram illustrating an example of an operation of a first position determining unit. FIG. [Diagram 5] 11A to 11C are diagrams illustrating an example of the operation of a second position determining section. [Figure 6] FIG. 2 illustrates an example of a hardware configuration of an inspection device. [Figure 7] 10 is a flowchart illustrating an example of a process performed by an inspection device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In all the drawings, the same components are given the same reference numerals and the description will be omitted as appropriate.

[0013] 1 is a diagram for explaining a usage environment of an inspection device 10 according to an embodiment. The inspection device 10 is used together with an imaging device 20. The imaging device 20 captures an object to be inspected, generates an image, and transmits the image to the inspection device 10. The inspection device 10 processes the image to determine whether the object to be inspected is good or bad.

[0014] Although not shown, when the imaging device 20 is imaging the object 30, the amount of light incident on the object 30 is constant. As an example, the relative positions of the light source and the imaging device 20 with respect to the object 30 during imaging are constant. This is because the inspection device 10 uses pixel values ​​of the image when determining the quality of the inspection object. If the image is a grayscale (monochrome image), the pixel value of each pixel is uniquely determined. On the other hand, if the image is a color image, the inspection device 10 may, for example, calculate pixel values ​​on the grayscale using pixel values ​​of each color and use these pixel values, or may use pixel values ​​of a specific color (for example, blue in RGB).

[0015] In the example shown in this figure, the inspection target is a part of the object 30. The object 30 is, for example, a printed matter such as a banknote, a pamphlet, or a poster, and the inspection target is a specific part of this printed matter. The inspection device 10 judges the quality of the inspection target, for example, the quality of the print density. The judgment speed at this time is, for example, 100 milliseconds or less per sheet, or even 20 milliseconds or less. When the object 30 is a banknote, the inspection target is a specific mark. This mark is, for example, at least a part of a euroion.

[0016] When the object 30 is a printed matter, the imaging device 20 generates an image immediately after the printed matter is printed, and transmits the image to the inspection device 10 in real time. The inspection device 10 judges the quality of the inspection object every time it acquires an image. When printed matters are printed continuously and all printed matters are inspected, the inspection device 10 and the imaging device 20 perform imaging and inspection continuously.

[0017] 2 is a diagram showing an example of a functional configuration of the inspection device 10. In the example shown in this figure, the inspection device 10 includes an inspection device 10, a first position determining unit 120, a second position determining unit 130, a determination unit 140, and an output unit 150.

[0018] The image acquisition unit 110 acquires the image generated by the imaging device 20 .

[0019] The first position determination unit 120 sets an area in the image acquired by the imaging device 20 where the first frame should be placed. The first frame preferably has a size capable of including the inspection object, but is not limited to this. The size of the first frame is, for example, 0.7 times or more and 1.5 times or less of the inspection object, but is not limited to this size. The first position determination unit 120 generates statistical data (hereinafter referred to as first data) of pixel values ​​inside the first frame at each position while moving the first frame in the area including the inspection object in the image. The first data is, for example, the variance of pixel values, but may be other statistical values ​​as long as it is an index indicating the magnitude of the variation in pixel values. Then, the first position determination unit 120 uses this first data to determine the position of the first frame.

[0020] The second position determination unit 130 moves the second frame, which is smaller than the first frame, within the first frame, and generates statistical data (hereinafter referred to as second data) of pixel values ​​within the second frame at each position. The size of the second frame is preferably capable of including the inspection object inside, and is, for example, 0.5 to 1.5 times the inspection object, but is not limited to this size. The second data is, for example, the variance of pixel values, but may be other statistical values ​​as long as it is an index indicating the magnitude of variation in pixel values. The second position determination unit 130 then determines the position of the second frame using the second data.

[0021] Here, it is assumed that the area surrounding the inspection target is plain (but may have a specific color) or has a color with less shading compared to the inspection target. In one example of such a case, the object 30 is a printed matter such as a banknote, and the inspection target is a mark.

[0022] The first frame includes the inspection object and the periphery of the inspection object. In this case, when the inspection object is located approximately in the center of the first frame, the variation in pixel values ​​within the first frame becomes large. Therefore, the first position determination unit 120 determines the position of the first frame so that the variation in pixel values ​​becomes the largest (for example, so that the variance becomes the largest). In the position determined by the first position determination unit 120, the first frame includes the inspection object inside. Note that, in one example of such a case, the object 30 is a printed matter such as a banknote, and the inspection object is a mark.

[0023] The second frame is smaller than the first frame. Therefore, the proportion of the area surrounding the inspection object in the second frame is smaller than that of the first frame. The size of the second frame is preferably approximately the same as or slightly larger than the inspection object. In this case, when the inspection object is positioned approximately in the center of the second frame, the variation in pixel values ​​within the second frame is small. Therefore, the second position determination unit 130 determines the position of the second frame so that the variation in pixel values ​​is minimized (for example, so that the variance is minimized). At the position determined by the second position determination unit 130, the second frame includes the inspection object inside.

[0024] The determination unit 140 determines whether or not there is an abnormality in the inspection target using data on pixel values ​​in the first frame (hereinafter referred to as third data) and data on pixel values ​​in the second frame (hereinafter referred to as fourth data).

[0025] For example, when the object 30 is a printed matter, the inspection object is a part of the printed matter, and the judgment unit 140 judges whether the density of the inspection object is light or not, an example of the third data is one of the maximum and minimum pixel values. In this case, the fourth data is the other of the maximum and minimum pixel values. For example, when the color of the inspection object is darker than the color of the base (surroundings) of the inspection object (for example, when a mark of a darker color than the base is printed on a white or light-colored base), the third data is the maximum pixel value, and the fourth data is the minimum pixel value. On the other hand, when the color of the inspection object is darker than the color of the base (surroundings) of the inspection object (for example, when a mark of a lighter color than the base is printed on a dark-colored base such as black), the third data is the minimum pixel value, and the fourth data is the maximum pixel value. Then, the judgment unit 140 judges the presence or absence of an abnormality using at least one of the ratio and difference between the third data and the fourth data. For example, when the third data is the maximum pixel value and the fourth data is the minimum pixel value, the judgment unit 140 judges that the density of the inspection object is abnormal if the third data / fourth data is equal to or less than the reference value. Furthermore, when the third data is the minimum pixel value and the fourth data is the maximum pixel value, the determination unit 140 determines that the density of the test object is abnormal when the fourth data / third data is equal to or less than the reference value. In either case, the determination unit 140 may determine that the density of the test object is abnormal when the difference between the third data and the fourth data is equal to or less than the reference value.

[0026] The determination unit 140 may arrange the pixels in the first frame in ascending (or descending) order of pixel value, calculate the average value of a predetermined number of pixels at the top, and use this average value as the third data. In this case, the determination unit 140 may arrange the pixels in the second frame in ascending (or descending) order of pixel value, calculate the average value of a predetermined number of pixels at the top, and use this average value as the fourth data. Furthermore, the determination unit 140 may use the average of the pixel values ​​in the first frame (excluding the second frame) as the third data, and the average of the pixel values ​​in the second frame as the fourth data.

[0027] The output unit 150 outputs the determination result of the determination unit 140. This output destination may be a display or a speaker. The output unit 150 may perform a predetermined output only when an object 30 having an abnormality is detected.

[0028] 3, 4, and 5, specific examples of the processes performed by the first position determining unit 120, the second position determining unit 130, and the determining unit 140 will be described. In these figures, the target object 30 is a printed matter such as a banknote.

[0029] 3 is a diagram showing an example of an image generated by the imaging device 20. In the example shown in this figure, the inspection object 32 is a mark printed on a substrate. In addition, the inspection object 32 is surrounded by a blank area 34, and the substrate is almost completely exposed. In addition, a predetermined pattern or the like is printed outside the blank area 34. The image 210 generated by the imaging device 20 includes the inspection object 32 and the blank area 34 inside, and also includes the area outside the blank area 34.

[0030] 4 is a diagram showing an example of the operation of the first position determination unit 120. The first frame 212 set by the first position determination unit 120 is sized so as to include as little of the area outside the margin area 34 as possible. For this reason, when the position of the first frame 212 is appropriately set (for example, so that the variation in pixel values ​​within the first frame 212 is maximized), the area of ​​the image 210 cut out by the first frame 212 (i.e., the area located inside the first frame 212) is almost entirely occupied by the inspection object 32 and the margin area 34.

[0031] FIG. 5 is a diagram showing an example of the operation of the second position determination unit 130. The second frame 214 set by the second position determination unit 130 is smaller than the first frame 212, but includes the inspection object 32 inside and is sized to include as little of the marginal area 34 as possible. Therefore, when the position of the second frame 214 is appropriately set within the first frame 212 (for example, so that the variation in pixel values ​​within the second frame 214 is minimized), the area of ​​the image 210 cut out by the second frame 214 (i.e., the area located inside the second frame 214) is almost entirely occupied by the inspection object 32. By performing such processing, the second position determination unit 130 can cut out the inspection object 32 from the image with high accuracy even if the image resolution is low. In addition, the inspection object 32 may be deformed due to temperature, humidity, etc. Even in such a case, the inspection object 32 can be cut out from the image with high accuracy.

[0032] When the color of the marginal area 34 is lighter than the color of the inspection object 32, or when the marginal area 34 is white, the maximum pixel value in the first frame 212 indicates the pixel value of the marginal area 34. The minimum pixel value in the second frame 214 indicates the pixel value of the inspection object 32. Therefore, by comparing the maximum pixel value in the first frame 212 with the minimum pixel value in the second frame 214, the determination unit 140 can determine whether or not there is an abnormality in the density of the inspection object 32.

[0033] On the other hand, if the color of the marginal area 34 is darker than the color of the inspection object 32, the minimum pixel value in the first frame 212 indicates the pixel value of the marginal area 34. Moreover, the maximum pixel value in the second frame 214 indicates the pixel value of the inspection object 32. Therefore, by comparing the minimum pixel value in the first frame 212 with the maximum pixel value in the second frame 214, the determination unit 140 can determine whether or not there is an abnormality in the density of the inspection object 32.

[0034] By carrying out such processing, the determination unit 140 can determine with high accuracy whether the inspection object 32 is good or bad, even if the image resolution is low.

[0035] Note that multiple inspection targets 32 may be set for one object 30. In this case, the inspection device 10 performs a process of generating third data and fourth data for each of the multiple inspection targets 32. Then, the determination unit 140 uses these multiple sets of third data and fourth data to determine the presence or absence of an abnormality in the object.

[0036] For example, the determination unit 140 may determine the presence or absence of an abnormality for each of the multiple inspection targets 32, and use these determination results to determine the presence or absence of an abnormality in the target object 30. In this case, the determination unit 140 determines that the target object 30 is abnormal when a predetermined rate or more of the inspection targets 32 are determined to be abnormal. Furthermore, when the multiple inspection targets 32 are the same mark printed in different locations (e.g., each is at least a part of a europium), the determination unit 140 may calculate an average value of the third data for each of the multiple inspection targets 32 and an average value of the fourth data for each of the multiple inspection targets 32, and use these two average values ​​instead of the third data and the fourth data.

[0037] 6 is a diagram showing an example of a hardware configuration of the inspection device 10. The inspection device 10 includes a bus 1010, a processor 1020, a memory 1030, a storage device 1040, an input / output interface 1050, and a network interface 1060.

[0038] The bus 1010 is a data transmission path for transmitting and receiving data among the processor 1020, memory 1030, storage device 1040, input / output interface 1050, and network interface 1060. However, the method of connecting the processor 1020 and the like to each other is not limited to bus connection.

[0039] The processor 1020 is implemented by a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or the like.

[0040] The memory 1030 is a main storage device realized by a RAM (Random Access Memory) or the like.

[0041] The storage device 1040 is an auxiliary storage device realized by a hard disk drive (HDD), a solid state drive (SSD), a memory card, a read only memory (ROM), or the like. The storage device 1040 stores program modules that realize each function of the inspection device 10 (e.g., the image acquisition unit 110, the first position determination unit 120, the second position determination unit 130, the determination unit 140, and the output unit 150). The processor 1020 loads each of these program modules onto the memory 1030 and executes them, thereby realizing each function corresponding to the program module.

[0042] The input / output interface 1050 is an interface for connecting the inspection device 10 to various input / output devices. For example, the inspection device 10 may communicate with the imaging device 20 via the input / output interface 1050.

[0043] The network interface 1060 is an interface for connecting the inspection device 10 to a network. This network is, for example, a LAN (Local Area Network) or a WAN (Wide Area Network). The method for connecting the network interface 1060 to the network may be a wireless connection or a wired connection. However, the inspection device 10 does not necessarily have to have the network interface 1060.

[0044] 7 is a flowchart showing an example of processing performed by the inspection device 10. When a new object 30 exists (for example, when a printed matter is newly printed as the object 30), the imaging device 20 captures the object 30 and generates an image. The inspection device 10 performs the processing shown in this figure every time the imaging device 20 generates an image. This processing is preferably performed in real time.

[0045] The image acquisition unit 110 of the inspection device 10 acquires the image transmitted from the imaging device 20 (step S10). Then, the first position determination unit 120 of the inspection device 10 determines the position of the first frame in this image (step S20). Next, the second position determination unit 130 of the inspection device 10 determines the position of the second frame within the first frame determined in step S20. At this time, when the second position determination unit 130 moves the second frame, it is preferable that the initial position of the second frame is set so as to include the center of the first frame (for example, so that the centers overlap) (step S30). Details of the processing performed in steps S20 and S30 are as described with reference to Figs. 2 to 5.

[0046] Next, the judgment unit 140 of the inspection device 10 judges whether the inspection object is good or bad (step S40). Details of the process performed in step S40 are as described with reference to Fig. 2 to Fig. 5. Then, the output unit 150 outputs the judgment result (step S50).

[0047] As described above, according to this embodiment, by using the inspection device 10, it is possible to judge the quality of the inspection object with high accuracy even when the resolution of the image generated by the imaging device 20 is low. In particular, when the inspection object is a printed matter and the base material of this printed matter is paper, the shape and size of the inspection object itself change depending on the temperature and humidity. More specifically, there are cases where the shape and size of the inspection object change depending on the temperature and humidity during printing, and cases where the shape and size of the inspection object change depending on the temperature and humidity during inspection. Even in such cases, by using the inspection device 10, it is possible to judge the quality of the inspection object with high accuracy.

[0048] Although the embodiments of the present invention have been described above with reference to the drawings, these are merely examples of the present invention, and various configurations other than those described above can also be adopted.

[0049] In addition, in the flowcharts used in the above description, multiple steps (processes) are described in order, but the order of execution of the steps performed in each embodiment is not limited to the order described. In each embodiment, the order of the steps shown in the figures can be changed to the extent that the content is not affected. In addition, the above-mentioned embodiments can be combined to the extent that the content is not contradictory.

[0050] A part or all of the above-described embodiments can be described as, but are not limited to, the following supplementary notes. 1. An image acquisition means for acquiring an image including an object to be inspected; a first position determination means for generating first data, which is statistical data of pixel values ​​within a first frame while moving the first frame in a region of the image including the inspection object, and determining a position of the first frame using the first data; a second position determination means for generating second data, which is statistical data of pixel values ​​within the second frame, while moving a second frame smaller than the first frame within the first frame, and determining a position of the second frame using the second data; a determination means for determining the presence or absence of an abnormality in the inspection object by using third data on the pixel values ​​in the first frame and fourth data on the pixel values ​​in the second frame; An inspection device comprising: 2. In the inspection device according to the above item 1, An inspection apparatus, wherein the first data and the second data are variances of the pixel values. 3. In the inspection device according to 1 or 2 above, An inspection device, wherein the inspection object is a part of a printed matter. 4. In the inspection device according to the above item 3, The inspection device, wherein the printed matter is a banknote. 5. In the inspection device according to 3 or 4 above, the third data relates to one of a maximum value and a minimum value of the pixel values; An inspection device, wherein the fourth data relates to the other of the maximum and minimum pixel values. 6. In the inspection device according to the above item 5, The determination means determines the presence or absence of the abnormality using at least one of a ratio and a difference between the third data and the fourth data. 7. In the inspection device according to 3 or 4 above, the third data is an average value of a predetermined number of top pixel values ​​when the pixel values ​​in the first frame are sorted in ascending or descending order, The fourth data is an average value of a predetermined number of top pixel values ​​when the multiple pixel values ​​in the second frame are sorted in ascending or descending order. 8. In the inspection device according to any one of 3 to 7 above, The printed matter has a plurality of the inspection targets, The determination means determines the presence or absence of the abnormality using the third data and the fourth data for each of the plurality of inspection objects. 9. The computer An image acquisition process for acquiring an image including an object to be inspected; a first position determination process for generating first data, which is statistical data of pixel values ​​within a first frame while moving the first frame in a region of the image including the inspection object, and determining a position of the first frame using the first data; a second position determination process for generating second data, which is statistical data of pixel values ​​within the second frame, while moving a second frame smaller than the first frame within the first frame, and determining a position of the second frame using the second data; a determination process for determining the presence or absence of an abnormality in the inspection object by using third data on the pixel values ​​in the first frame and fourth data on the pixel values ​​in the second frame; An inspection method. 10. In the inspection method according to 9 above, An inspection method, wherein the first data and the second data are variances of the pixel values. 11. In the inspection method according to 9 or 10 above, An inspection method, wherein the inspection object is a part of a printed matter. 12. In the inspection method according to 11 above, The inspection method, wherein the printed matter is a banknote. 13. In the inspection method according to 11 or 12 above, the third data relates to one of a maximum value and a minimum value of the pixel values; An inspection method, wherein the fourth data relates to the other of the maximum and minimum values ​​of the pixel values. 14. In the inspection method according to 13 above, An inspection method, wherein in the determination process, the computer determines the presence or absence of the abnormality using at least one of a ratio and a difference between the third data and the fourth data. 15. In the inspection method according to 11 or 12 above, the third data is an average value of a predetermined number of top pixel values ​​when the pixel values ​​in the first frame are sorted in ascending or descending order, An inspection method, wherein the fourth data is an average value of a predetermined number of top pixel values ​​when the multiple pixel values ​​in the second frame are sorted in ascending or descending order. 16. In the inspection method according to any one of the above 11 to 15, The printed matter has a plurality of the inspection targets, An inspection method, wherein in the judgment process, the computer judges the presence or absence of the abnormality using the third data and the fourth data for each of the multiple inspection objects. 17. To the computer: an image acquisition function for acquiring an image including an object to be inspected; a first position determination function that generates first data, which is statistical data of pixel values ​​within a first frame, while moving the first frame in a region of the image that includes the inspection object, and determines a position of the first frame using the first data; a second position determination function that generates second data, which is statistical data of pixel values ​​within the second frame, while moving a second frame smaller than the first frame within the first frame, and determines a position of the second frame using the second data; a determination function for determining the presence or absence of an abnormality in the inspection object by using third data on the pixel values ​​in the first frame and fourth data on the pixel values ​​in the second frame; A program that allows you to have 18. In the program according to 17 above, The first data and the second data are variances of the pixel values. 19. In the program according to 17 or 18 above, A program in which the object to be inspected is a part of a printed matter. 20. In the program according to claim 19, The program, wherein the printed matter is a banknote. 21. In the program according to 19 or 20 above, the third data relates to one of a maximum value and a minimum value of the pixel values; The fourth data relates to the other of the maximum and minimum values ​​of the pixel values. 22. In the program according to 21 above, The determination function determines the presence or absence of the abnormality using at least one of a ratio and a difference between the third data and the fourth data. 23. In the program according to 19 or 20 above, the third data is an average value of a predetermined number of top pixel values ​​when the pixel values ​​in the first frame are sorted in ascending or descending order, The fourth data is an average value of a predetermined number of top pixel values ​​when the multiple pixel values ​​in the second frame are sorted in ascending or descending order. 24. In the program according to any one of the above 19 to 23, The printed matter has a plurality of the inspection targets, The determination function is a program that determines the presence or absence of the abnormality using the third data and the fourth data for each of the multiple inspection objects. [Explanation of symbols]

[0051] 10 Inspection equipment 20 Imaging device 30 Objects 32 Test subjects 34 Margin Area 110 Image acquisition unit 120 1st position determination section 130 Second position determining section 140 Judgment section 150 Output section 210 images 212 First Pattern 214 Second Pattern

Claims

1. An image acquisition means for acquiring an image including an inspection object; a first position determination means for generating first data, which is statistical data of pixel values ​​within a first frame while moving the first frame in a region of the image including the inspection object, and determining a position of the first frame using the first data; a second position determination means for generating second data which is statistical data of pixel values ​​within the second frame while moving a second frame smaller than the first frame within the first frame whose position has been determined by the first position determination means, and determining a position of the second frame using the second data; a determination means for determining the presence or absence of an abnormality in the inspection object by using third data on the pixel values ​​in the first frame and fourth data on the pixel values ​​in the second frame; Equipped with The inspection target is a part of a printed matter, that is, a mark printed on a base, A margin area is present around the inspection target, When the inspection object is darker than the background, the third data relates to a maximum value of the pixel value, and the fourth data relates to a minimum value of the pixel value. When the object to be inspected is thinner than the base, the third data relates to a minimum value of the pixel value, and the fourth data relates to a maximum value of the pixel value.

2. 2. The inspection device according to claim 1, An inspection apparatus, wherein the first data and the second data are variances of the pixel values.

3. 3. The inspection device according to claim 1, The inspection device, wherein the printed matter is a banknote.

4. In the inspection device according to any one of claims 1 to 3, The determination means determines the presence or absence of the abnormality using at least one of a ratio and a difference between the third data and the fourth data.

5. 3. The inspection device according to claim 1, the third data is an average value of a predetermined number of top pixel values ​​when the plurality of pixel values ​​in the first frame are sorted in ascending or descending order, The fourth data is an average value of a predetermined number of top pixel values ​​when the multiple pixel values ​​in the second frame are sorted in ascending or descending order.

6. In the inspection device according to any one of claims 1 to 5, The printed matter has a plurality of the inspection targets, The determination means determines the presence or absence of the abnormality using the third data and the fourth data for each of the plurality of inspection objects.

7. The computer An image acquisition process for acquiring an image including an object to be inspected; a first position determination process for generating first data, which is statistical data of pixel values ​​within a first frame, while moving the first frame in a region of the image including the inspection object, and determining a position of the first frame using the first data; a second position determination process for generating second data, which is statistical data of pixel values ​​within the second frame, while moving a second frame smaller than the first frame within the first frame whose position has been determined by the first position determination process, and determining a position of the second frame using the second data; a determination process for determining the presence or absence of an abnormality in the inspection object by using third data on the pixel values ​​in the first frame and fourth data on the pixel values ​​in the second frame; Do the following: The inspection target is a part of a printed matter, that is, a mark printed on a base, A margin area is present around the inspection target, When the inspection object is darker than the background, the third data relates to a maximum value of the pixel value, and the fourth data relates to a minimum value of the pixel value. When the object to be inspected is thinner than the base, the third data relates to a minimum value of the pixel value, and the fourth data relates to a maximum value of the pixel value.

8. On the computer, an image acquisition function for acquiring an image including an object to be inspected; a first position determination function that generates first data, which is statistical data of pixel values ​​within a first frame while moving the first frame in a region of the image that includes the inspection object, and determines a position of the first frame using the first data; a second position determination function that generates second data, which is statistical data of pixel values ​​within the second frame, while moving a second frame smaller than the first frame within the first frame whose position has been determined by the first position determination function, and determines the position of the second frame using the second data; a determination function for determining the presence or absence of an abnormality in the inspection object by using third data on the pixel values ​​in the first frame and fourth data on the pixel values ​​in the second frame; Let them have The inspection target is a part of a printed matter, that is, a mark printed on a base, A margin area is present around the inspection target, When the inspection object is darker than the background, the third data relates to a maximum value of the pixel value, and the fourth data relates to a minimum value of the pixel value. When the object to be inspected is thinner than the base, the third data relates to a minimum value of the pixel value, and the fourth data relates to a maximum value of the pixel value.

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