Inspection method and inspection apparatus

Abstract

This disclosure provides an inspection method and an inspection apparatus. The inspection apparatus includes an imaging element comprising: a first imaging region including a plurality of first pixels, wherein the plurality of first pixels capture an image of an object in a first band and output a plurality of first feature quantities; and a reference imaging region including a plurality of reference pixels, wherein the plurality of reference pixels capture an image of an object in a reference band overlapping with the first band and output a plurality of reference feature quantities. An image processing apparatus determines the reflectance of the object in the first band based on at least one of the plurality of first feature quantities and at least one of the plurality of reference feature quantities, and determines the physical properties of the object (E) based on the reflectance. The image processing apparatus corrects the image of the object generated based on the output from the imaging element based on at least one of the plurality of first feature quantities and at least one of the plurality of reference feature quantities.

Description

Technical Field

[0001] This disclosure relates to an inspection device and an inspection method for an object to be inspected. Background Technology

[0002] In the fields of semiconductors, electronic devices, and secondary batteries, there are known inspection devices that use image sensors to detect objects (foreign objects, defects, etc.) on the inspected object.

[0003] In Patent Document 1, multiple spectral images are generated, and the feature values ​​of the spectral images are compared with the feature values ​​of normal data to detect foreign objects (objects) mixed into the object under inspection (subject). That is, Patent Document 1 uses the difference in physical properties between the subject and the object to detect the object.

[0004] Prior art literature

[0005] Patent documents

[0006] Patent Document 1: Japanese Patent Application Publication No. 2016-138789 Summary of the Invention

[0007] One embodiment of this disclosure relates to an inspection method for detecting objects contained in an inspected object by means of an inspection device taking an image. The inspection device includes an imaging element comprising: a first imaging region containing a plurality of first pixels, the plurality of first pixels capturing an image of the object in a first band and outputting a plurality of first feature quantities; and a reference imaging region containing a plurality of reference pixels, the plurality of reference pixels capturing an image of the object in a reference band overlapping with the first band and outputting a plurality of reference feature quantities. The inspection method includes: a reflectance calculation step, calculating the reflectance of the object in the first band, i.e., a first reflectance, based on at least one of the plurality of first feature quantities and at least one of the plurality of reference feature quantities; a property determination step, determining the property of the object based on the first reflectance; and an image correction step, correcting the image of the object generated based on the output from the imaging element, based on at least one of the plurality of first feature quantities and at least one of the plurality of reference feature quantities.

[0008] Another embodiment of this disclosure relates to an inspection method for detecting objects contained in an inspected object by means of an inspection device taking an image. The inspection device includes an imaging element comprising: a first imaging region containing a plurality of first pixels, the plurality of first pixels capturing an image of the object in a first band and outputting a plurality of first feature values; a second imaging region containing a plurality of second pixels, the plurality of second pixels capturing an image of the object in a second band and outputting a plurality of second feature values; and a reference imaging region containing a plurality of reference pixels, the plurality of reference pixels capturing an image of the object in a reference band overlapping with the first band and the second band and outputting a plurality of reference feature values. The inspection method includes a reflectance calculation step. The process includes: a first reflectance (i.e., the first reflectance) and a second reflectance (i.e., the second reflectance) of the object in the first band, based on at least one of the plurality of first feature quantities, at least one of the plurality of second feature quantities, and at least one of the plurality of reference feature quantities; a property determination step, determining the property of the object based on the first reflectance and the second reflectance; an image correction step, correcting the image of the object generated based on the output from the imaging element based on at least one of the plurality of first feature quantities, at least one of the plurality of second feature quantities, and at least one of the plurality of reference feature quantities; and a size determination step, determining the size of the object based on the image of the object corrected in the image correction step.

[0009] One embodiment of this disclosure relates to an inspection apparatus for detecting objects contained in an inspected object. The apparatus includes an imaging element and an image processing unit. The imaging element comprises: a first imaging region including a plurality of first pixels, wherein the plurality of first pixels capture an image of the object in a first band and output a plurality of first feature quantities; and a reference imaging region including a plurality of reference pixels, wherein the plurality of reference pixels capture an image of the object in a reference band overlapping with the first band and output a plurality of reference feature quantities. The image processing unit calculates the reflectance, i.e., a first reflectance, of the object in the first band based on at least one of the plurality of first feature quantities and at least one of the plurality of reference feature quantities; determines the physical properties of the object based on the first reflectance; corrects the image of the object generated from the output of the imaging element based on at least one of the plurality of first feature quantities and at least one of the plurality of reference feature quantities; and determines the size of the object based on the corrected image of the object.

[0010] Another embodiment of this disclosure relates to an inspection apparatus for detecting objects contained in an inspected object. The apparatus includes an imaging element and an image processing unit. The imaging element comprises: a first imaging region including a plurality of first pixels, wherein the plurality of first pixels capture an image of the object in a first band and output a plurality of first feature values; a second imaging region including a plurality of second pixels, wherein the plurality of second pixels capture an image of the object in a second band and output a plurality of second feature values; and a reference imaging region including a plurality of reference pixels, wherein the plurality of reference pixels capture an image of the object in a reference band overlapping with the first band and the second band and output a plurality of reference feature values. The image processing device calculates the reflectance (i.e., the first reflectance) in the first band and the reflectance (i.e., the second reflectance) in the second band of the object based on at least one of the plurality of first features, at least one of the plurality of second features, and at least one of the plurality of reference features; determines the physical properties of the object based on the first reflectance and the second reflectance; corrects the image of the object generated based on the output from the imaging element based on at least one of the plurality of first features, at least one of the plurality of second features, and at least one of the plurality of reference features; and determines the size of the object based on the corrected image of the object. Attached Figure Description

[0011] Figure 1 This is a side view of the inspection device according to the first embodiment.

[0012] Figure 2 This is a top view of the inspection device according to the first embodiment.

[0013] Figure 3 This is a top view showing the structure of the imaging element according to the first embodiment.

[0014] Figure 4 This is a flowchart illustrating the overall operation of the image processing apparatus according to the first embodiment.

[0015] Figure 5 This is a diagram showing an example of an image of a sheet captured by the imaging element according to the first embodiment.

[0016] Figure 6 This is a diagram showing an example of the brightness value of a sheet captured by the imaging element according to the first embodiment.

[0017] Figure 7 This is a flowchart illustrating the process of determining the physical properties of the image processing apparatus according to the first embodiment.

[0018] Figure 8It is a graph showing the spectrophotometric reflectance curves representing the spectrophotometric reflectance of multiple substances.

[0019] Figure 9 This is a flowchart illustrating the process of correcting image processing in the image processing apparatus according to the first embodiment.

[0020] Figure 10A This is a diagram showing the extracted image before correction.

[0021] Figure 10B This is a diagram showing the corrected image.

[0022] Figure 11A This is a diagram showing the extracted image before correction.

[0023] Figure 11B This is a diagram showing the corrected image.

[0024] Figure 12A This is a diagram showing the extracted image before correction.

[0025] Figure 12B This is a diagram showing the corrected image.

[0026] Figure 13 This is a diagram showing an example of a corrected image of the sheet material according to the first embodiment.

[0027] Figure 14A This is a diagram used to explain the method for determining the size of an object according to the first embodiment.

[0028] Figure 14B This is a diagram used to explain the method for determining the size of an object according to the first embodiment.

[0029] Figure 14C This is a diagram used to explain the method for determining the size of an object according to the first embodiment.

[0030] Figure 15 This is a top view showing the structure of the imaging element according to the second embodiment.

[0031] Figure 16 This is a diagram showing an example of an image of a sheet captured by the imaging element according to the second embodiment.

[0032] Figure 17 This is a diagram showing an example of the brightness value of a sheet captured by the imaging element according to the second embodiment.

[0033] Figure 18 This is a flowchart illustrating the process of determining the physical properties of the image processing apparatus according to the second embodiment.

[0034] Figure 19It is a graph showing a chart of reflectivity according to the second embodiment.

[0035] Symbol Explanation

[0036] A. Inspection device;

[0037] 1. Filming device;

[0038] 6. Image processing device;

[0039] 10 pixels;

[0040] 11. Imaging components;

[0041] 13. First shooting area;

[0042] 14. Baseline shooting area;

[0043] 16. Second shooting area;

[0044] 17. Third shooting area;

[0045] E(E1~E3) Objects;

[0046] P-image;

[0047] p Extract the image;

[0048] pw is used to correct images. Detailed Implementation

[0049] When using the technology in Patent Document 1, in order to generate a spectroscopic image with multiple wavelengths, the pixels of the imaging element need to be allocated according to each band. Therefore, the resolution of the spectroscopic image for each band is lower than that of the image obtained based on the resolution of the imaging element. Consequently, the image containing the object becomes coarse, for example, the accuracy of object size measurement decreases.

[0050] Therefore, the purpose of this disclosure is to provide an inspection method and apparatus that can determine the physical properties of an object while suppressing the decrease in resolution of the image obtained from the imaging element.

[0051] Hereinafter, embodiments of the present disclosure will be described in detail based on the accompanying drawings. The following description of preferred embodiments is merely illustrative in nature and is not intended to limit the present disclosure, its applications, or its uses.

[0052] Figure 1 A side view of the inspection device is shown. Figure 2 A top view of the inspection device is shown. (Example) Figure 1 as well as Figure 2 As shown, the inspection device A includes a camera 1, a lighting device 2, rollers 3-5, and an image processing device 6. A conveyor belt 7 is wound around the outer periphery of the rollers 3-5.

[0053] Inspection device A inspects sheet S (the object to be inspected). Sheet S is used, for example, in the fields of semiconductors, electronic devices, and secondary batteries. In the following description, the case where the object to be inspected is sheet-shaped is used as an example, but the object to be inspected may not be sheet-shaped. Furthermore, if sheet S is a long strip, sheet S is wound around rollers 3-5 instead of conveyor belt 7. Then, sheet S is conveyed by rollers 3-5 in the direction of arrow D.

[0054] Inspection device A detects defects, foreign objects, and other objects E contained in sheet S. These defects include, for example, not only incomplete or insufficient portions of sheet S due to manufacturing defects such as shortness or broken threads, but also damage to sheet S (e.g., scratches caused by contact between sheet S and other components). If the detected object E is larger than a given size, the inspection device determines that sheet S contains an object. Furthermore, sheet S is placed on conveyor belt 7 and moved along... Figure 1 as well as Figure 2 The direction of arrow D, indicated by the solid line, is being transported.

[0055] The imaging device 1 includes an imaging element 11 to photograph the sheet S conveyed by the conveyor belt 7. Here, the imaging device 1 is configured as a region sensor that photographs the entire sheet S between the rollers 4 and 5. Alternatively, the imaging device 1 can also be configured as a row sensor instead of a region sensor.

[0056] The imaging device 1 sends the pixel signal output from the imaging element 11 to the image processing device 6. Furthermore, in the following description, the scanning direction of the imaging device 1 is defined as the X direction, the sub-scanning direction of the imaging device 1 is defined as the Y direction, and the direction perpendicular to both the X and Y directions is defined as the Z direction.

[0057] The illumination device 2, for example, has a light source composed of LEDs, lasers, halogen light sources, etc., which illuminates the scanning area (sheet S) of the imaging device 1 between rollers 4 and 5. Specifically, the illumination direction of the light from the illumination device 2 is set to an incident angle of approximately 10° relative to the conveyor belt 7. Furthermore, the imaging device 1 and the illumination device 2 can be configured as a dark-field optical system, so that the light emitted by the illumination device 2 does not directly incident on the imaging element 11. Although the imaging device 1 and the illumination device 2 can also be configured as a bright-field optical system, it is preferable to use a dark-field optical system. By using a dark-field optical system, illumination can be provided at a low angle relative to the object E, thus making the substrate of the object E less bright (the brightness of the substrate (ground level) without foreign objects becomes low grayscale). As a result, the brightness of the object E is higher than that of the substrate, and the SN (signal-to-noise ratio) is improved, thus enabling the generation of a clear image of the object E.

[0058] Roller 3 rotates via a drive mechanism (not shown in the figure), thereby driving conveyor belt 7 to convey sheet S along the direction of the solid arrow in the figure.

[0059] The image processing apparatus 6 is, for example, a computer. The image processing apparatus 6 determines the physical properties and size of the object E based on pixel signals received from the imaging device 1 (imaging element 11). Specifically, the image processing apparatus 6 performs image extraction processing, physical property determination processing, image correction processing, and size determination processing, which will be described later.

[0060] Furthermore, the structure of the inspection device A is not limited to the structure described above.

[0061] Alternatively, the inspection device A may be equipped with a rotary encoder that detects the rotational speed of rollers 3 to 5. In this case, the amount of movement of the sheet S conveyed by the conveyor belt 7 can also be detected based on the detection result of the rotary encoder.

[0062] Furthermore, the film S can be photographed either while the film S or the shooting device 1 is moving, or when the film S or the shooting device 1 is stationary.

[0063] (First Embodiment)

[0064] (Regarding the structure of the imaging element)

[0065] Figure 3 This is a top view showing the structure of the imaging element according to the first embodiment. The imaging element 11 is, for example, a CMOS (Complementary MOS) sensor.

[0066] like Figure 3 As shown, in the imaging element 11, m elements are formed in the X direction and n elements are formed in the Y direction (in... Figure 3 The pixel array 12 consists of 508×508 pixels arranged in a grid pattern. Furthermore, in the following description, the i-th pixel 10 in the X direction and the j-th pixel 10 in the Y direction is sometimes referred to as pixel (Xi, Yj).

[0067] Pixel array 12 includes pixels 10 allocated to the first shooting area 13 and pixels 10 allocated to the reference shooting area 14. Figure 3 In the first shooting area 13, pixels 10 where i is odd and j is even, and pixels 10 where i is even and j is odd, are assigned to pixels (Xi, Yj). Similarly, pixels 10 where i is odd and j is odd, and pixels 10 where i is even and j is even, are assigned to the reference shooting area 14. That is, in... Figure 3 In this configuration, the pixels 10 assigned to the first shooting area 13 and the reference shooting area 14 are arranged adjacent to each other.

[0068] An optical interference filter is provided on the pixel 10 of the first imaging region 13 to allow light of the first band to pass through. That is, the first imaging region 13 is the region where the pixel 10 is configured to capture the spectral image of the first band. In this embodiment, the first band is set to the red band (625-780nm).

[0069] The reference imaging area 14 is the area where pixels 10 are configured to capture images of a reference band including the first band. In this embodiment, the reference band is set to 400–800 nm. Furthermore, the reference band does not necessarily need to include the entire first band; it only needs to include a portion of it. For example, if the first band is 625–780 nm, the reference band can be 400–700 nm. That is, the reference band only needs to overlap with the first band.

[0070] (Regarding the operation of the image processing device)

[0071] Reference Figures 4 to 14C The inspection method for the subject according to the first embodiment will be described. Figure 4 This is a flowchart illustrating the overall operation of the image processing apparatus according to the first embodiment.

[0072] The imaging device 1 (imaging element 11) captures images of the sheet S conveyed by the conveyor belt 7 between rollers 4 and 5. The image processing device 6 acquires (receives) the pixel signal output from the imaging device 1 (step S1).

[0073] Based on the pixel signals acquired from the imaging device 1, the image processing device 6 generates an image P of the sheet S (step S2). Then, the image processing device 6 performs the image extraction processing described later to generate an extracted image p (step S3).

[0074] Image processing device 6 determines whether image P contains the extracted image p of object E (step S4). If image processing device 6 determines that image P does not contain the extracted image p of object E ("No" in step S4), the processing ends. That is, image processing device 6 determines that sheet S does not contain object E.

[0075] When the image processing device 6 determines that the image P contains the extracted image p of the object E ("Yes" in step S4), it performs the property determination process described later (step S5) to determine the property of the object E.

[0076] After step S5, the image processing device 6 performs the image correction process described later (step S6) to generate a corrected image pw that corrects the extracted image p. The image processing device 6 uses the generated corrected image pw to determine the size of the object E (step S7).

[0077] (Regarding image extraction and processing)

[0078] Below, refer to Figure 5 as well as Figure 6 The image extraction and processing of the image processing device 6 will be explained. Figure 5 This is a diagram showing an example of an image of a sheet captured by the imaging element according to the first embodiment. Figure 6 This is a diagram showing an example of the brightness value of a sheet captured by the imaging element according to the first embodiment.

[0079] In step S2, the image processing device 6 generates a pixel signal based on the pixel signal acquired from the imaging element 11. Figure 5 Image P of sheet S is shown. Additionally, in Figure 5 In the image, the photograph was taken with the sheet S contained within the dotted line portion. Furthermore, in the following description, the image data corresponding to pixel (Xi, Yj) is defined as image (xi, yj).

[0080] Then, in step S3, the image processing device 6 performs image extraction processing. Specifically, the image processing device 6 extracts the extracted image p of the object E based on the feature quantities of each image (xi, yj) in the image P. For example, the brightness value, lightness, etc., of each image (xi, yj) in the image P can be listed. Furthermore, the feature quantities can also be defined based on the feature quantities of the sheet S that does not contain the object E. In addition, the presence or absence of the object E is determined using feature quantities such as the area value, dimension in the X direction, dimension in the Y direction, shape, and total density of the object E. In this embodiment, the case where the feature quantity is the brightness value of each image (xi, yj) in the image P will be used as an example for explanation.

[0081] Figure 6 The brightness values ​​for each image (xi, yj) in image P are shown. Figure 6 In this system, brightness values ​​are represented using 8 bits of 256 grayscale, with a minimum value of 0 and a maximum value of 255. Figure 6 In the case where there is no object E (groundlevel) in the sheet S, the brightness value becomes 0.

[0082] First, the image processing device 6 extracts images (xi, yj) with brightness values ​​above a threshold. Then, the image processing device 6 treats multiple adjacent images (xi, yj) from the extracted images as a single object E. Here, "adjacent images" refers to images that are connected relative to a single image in the X-direction (horizontal), Y-direction (vertical), X-direction (horizontal), and Y-direction (tilt). Specifically, if the image is (xi, yj), then images (xi, yj±1), (xi±1, yj), and (xi±1, yj±1) are considered adjacent images. The image processing device 6 generates the extracted image in a manner that includes the extracted object E.

[0083] For example, in Figure 6 In the image processing unit 6, with the brightness threshold set to 20, the image processing unit 6 extracts the region of the image (xi, yj) surrounded by the dashed lines as objects E1 to E3. Then, the image processing unit 6 generates extracted images p1 to p3 (refer to...) in a manner that each contains objects E1 to E3. Figure 5 as well as Figure 6 Specifically, as the extracted image p1, the image contained in the region of image (x4, y2) to image (x11, y8) is extracted. As the extracted image p2, the image contained in the region of image (x14, y2) to image (x20, y6) is extracted. As the extracted image p3, the image contained in the region of image (x12, y8) to image (x22, y14) is extracted.

[0084] In addition, in step S4, if an extracted image p is generated from image P, the image processing device 6 determines that image P contains the extracted image p of object E.

[0085] (Regarding the handling of physical property determination)

[0086] Below, refer to Figures 5-8 The physical property determination process (step S5) of the image processing device 6 will be explained. Figure 7 This is a flowchart illustrating the process of determining the physical properties of the image processing apparatus according to the first embodiment.

[0087] If the image processing device 6 acquires the extracted image p (in) Figure 5 as well as Figure 6 In step S11, images p1 to p3 are extracted. Then, from the images included in the extracted images p, the image δ that corresponds to the pixel 10 of the reference shooting area 14 and has the highest feature quantity is extracted (step S12). Then, from the images adjacent to the extracted image δ, the image α that corresponds to the pixel 10 of the first shooting area 13 and has the highest feature quantity is extracted (step S13). The term "adjacent image" here refers to images that are connected relative to an image in the X direction (horizontal), Y direction (vertical), X direction, and Y direction (tilt direction).

[0088] If reference Figure 5 In the extracted images p1 to p3, images δ1 to δ3 (brightness values ​​255, 255, 255) are respectively equivalent to image δ, and images α1 to α3 (brightness values ​​155, 230, 204) are respectively equivalent to image α.

[0089] Following step S13, the reflectance R of the object E in the first band is calculated based on the feature values ​​(brightness values) of image δ and image α (step S14). Specifically, the reflectance R can be calculated by (brightness value of image α) / (brightness value of image δ). Pixel 10 of the first shooting area 13 corresponding to image α is a pixel that captures the spectral image of the first band, and pixel 10 of the reference shooting area 14 corresponding to image δ is a pixel that captures the spectral image of a reference band containing the first band. Therefore, by comparing the brightness values ​​(feature values) of image α and image δ, the reflectance R of the object E in the first band can be calculated.

[0090] For example, in Figure 5 In the above, the reflectance of object E1 is R1 = 155 / 255 ≈ 0.60, so the reflectance R1 of object E1 is 60%. The reflectance of object E2 is R2 = 230 / 255 ≈ 0.90, so the reflectance R2 of object E2 is 90%. The reflectance of object E3 is R3 = 204 / 255 = 0.80, so the reflectance R3 of object E3 is 80%.

[0091] After step S14, the image processing device 6 determines the physical properties of the object E based on the calculated reflectance R (step S15). Specifically, the image processing device 6 determines the physical properties of the object E based on a preset threshold. This threshold is based on a spectrophotometer curve representing the spectrophotometer reflectance of multiple substances (spectral reflectance data, refer to...). Figure 8 The image processing device 6 compares the reflectance R with a threshold to determine the physical properties of the object E.

[0092] exist Figure 8The image shows the spectrophotometric reflectance curves of Al, Fe, and Cu in various wavelength bands. Band 1 is 625–780 nm. Therefore, it can be determined that: when the reflectance is 50%–70%, object E is Fe; when the reflectance is 70%–90%, object E is Cu; and when the reflectance is above 90%, object E is Al. Specifically, object E1 has a reflectance R1 of 60%, therefore object E1 is determined to be Fe. Object E2 has a reflectance R2 of 90%, therefore object E2 is determined to be Al. Object E3 has a reflectance R3 of 80%, therefore object E3 is determined to be Fe. Thus, by setting a threshold for determining the properties of object E based on the spectrophotometric reflectance curves, the properties of object E can be determined.

[0093] Furthermore, the method for calculating reflectance R is not limited to the method described above. For example, reflectance R can also be obtained using the following method.

[0094] First, the image of object E is extracted from the extracted image p. Then, the image excluding the surrounding 1 pixel of object E is extracted. Thus, object E, which exists throughout the entire area of ​​the extracted image p, can be extracted.

[0095] Then, in the extracted image of object E, an average brightness value α' is calculated for the brightness values ​​of the image corresponding to pixel 10 in the first shooting area 13. Furthermore, in the extracted image of object E, an average brightness value δ' is calculated for the brightness values ​​of the image corresponding to pixel 10 in the reference shooting area 14. Then, the reflectance R of object E in the first band is calculated based on the average brightness value α' and the average brightness value δ'. Specifically, the reflectance R is calculated by (average brightness value α') / (average brightness value δ'). In this way, by averaging the brightness values ​​used in calculating the reflectance, errors in reflectance caused by singularities can be reduced.

[0096] Furthermore, the target object E can also detect substances other than metals. For example, it can also detect resins. Resin has low reflectivity in the visible light region and high reflectivity in the infrared region. Therefore, when detecting resins, it is necessary to expand the first band and the reference band to 1000 nm for detection.

[0097] (Image retouching)

[0098] Below, refer to Figures 9-13 The corrected image processing (step S6) of the image processing device 6 will be explained. Figure 9 This is a flowchart illustrating the process of correcting image processing in the image processing apparatus according to the first embodiment.

[0099] If the image processing device 6 acquires the extracted image p (p1 to p3) and the reflectance R (R1 to R3) (step S21), it corrects the image of the extracted image p (step S22). Then, the image processing device 6 generates a corrected image pw that has been corrected from the extracted image p (step S23).

[0100] Figure 10A The extracted image p1 before correction and its brightness value are shown. Figure 10B The corrected image pw1 and its brightness value are shown. Figure 11A The extracted image p2 before correction and its brightness value are shown. Figure 11B The corrected image pw2 and its brightness value are shown. Figure 12A The extracted image p3 and its brightness value are shown before correction. Figure 12B The corrected image pw3 and its brightness values ​​are shown.

[0101] like Figure 10A , Figure 11A as well as Figure 12A As shown, the image corresponding to pixel 10 of the first imaging region 13 has a lower brightness value compared to the image corresponding to pixel 10 of the reference imaging region 14. This is because pixel 10 of the first imaging region 13 generates a spectral image with a first band narrower than the reference band. Therefore, by correcting the brightness value of the image corresponding to pixel 10 of the first imaging region 13 to the same level as the brightness value of the image corresponding to pixel 10 of the reference imaging region 14, a clear image of the object E can be obtained.

[0102] For example, the above correction can be performed by dividing the brightness value of each image corresponding to pixel 10 of the first shooting area 13 by the reflectance R. By performing such correction on the extracted images p1 to p3 before correction, it is possible to generate images such as... Figure 10B , Figure 11B as well as Figure 12B Such a corrected image pw (pw1~pw3). By replacing the corrected image pw with the position of the extracted image p of image P, thus achieving... Figure 13 That way, a clear image PW of the object E can be obtained.

[0103] Furthermore, the correction process in step S22 is not limited to the method described above. For example, the brightness value of the image corresponding to pixel 10 of the first shooting area 13 may be set as the average of the brightness values ​​above a threshold among the images adjacent to that image and corresponding to pixel 10 of the reference shooting area 14.

[0104] For example, in Figure 5 as well as Figure 10AIn the process of correcting image (X6, Y3), the average of the brightness values ​​of adjacent images (X6, Y2), (X5, Y3), (X7, Y3), and (X6, Y4) becomes the brightness value of image (X6, Y3). The brightness value of image (X6, Y2) is 0, therefore it is excluded from averaging. Here, the brightness value of image (X6, Y3) = (50 + 255 + 255) / 3 ≈ 187. Thus, the brightness value of the image corresponding to pixel 10 of the first shooting area 13 can also be corrected based on the brightness value of the image corresponding to pixel 10 of the reference shooting area 14.

[0105] (Regarding the determination of the size of an object)

[0106] Below, refer to Figures 14A-14C The size determination process (step S7) of the image processing device 6 will be explained. Figures 14A-14C This diagram is used to explain the method for determining the size of an object according to the first embodiment. Specifically, Figures 14A-14C The following are examples of pairs of values ​​with a brightness value of 30 as the threshold: Figure 10B , Figure 11B as well as Figure 12B The corrected images pw1' to pw3' are obtained by binarizing the corrected images pw1 to pw3.

[0107] The dimensions of object E can be defined by area, maximum length, aspect ratio, width, length, Feret diameter (maximum and minimum values), and length of the main axis (maximum and minimum values). In this embodiment, the dimensions of object E will be explained using the case of determining the maximum Feret diameter F as an example. The Feret diameter refers to the length of the rectangle circumscribed around the object, both vertically and horizontally. The maximum Feret diameter represents the largest length among the rectangles circumscribed around the object.

[0108] exist Figures 14A-14C In the diagram, the length indicated by the arrow represents the maximum Freette diameter of objects E1 to E3. Therefore, the dimensions of objects E1 to E3 can be determined.

[0109] As described above, the inspection device A includes an imaging element 11, which has: a first imaging region 13 containing a plurality of first pixels 10, the plurality of first pixels 10 capturing an image of an object E in a first band and outputting a plurality of brightness values ​​(first feature quantities); and a reference imaging region 14 containing a plurality of reference pixels 10, the plurality of reference pixels 10 capturing an image of the object E in a reference band overlapping with the first band and outputting a plurality of brightness values ​​(reference feature quantities). The image processing device 6 calculates the reflectance R (first reflectance) of the object E in the first band based on at least one of the plurality of brightness values ​​(first feature quantities) and at least one of the plurality of brightness values ​​(reference feature quantities), and determines the physical properties of the object E based on the reflectance R. The image processing device 6 corrects the image of the object E generated based on the output from the imaging element 11 based on the reflectance R. That is, the reflectance R in the first band of the object E is calculated based on the brightness value output by pixel 10 in the first shooting area 13 and the brightness value output by pixel 10 in the reference shooting area 14, thus enabling the determination of the physical properties of the object E. Furthermore, the image output from the shooting element 11 is corrected based on the calculated reflectance R, thereby suppressing the decrease in resolution of the image obtained from the shooting element. Therefore, the physical properties of the object can be determined while suppressing the decrease in resolution of the image obtained from the shooting element.

[0110] Furthermore, the reflectance R is calculated based on the maximum brightness value among multiple brightness values ​​output by pixel 10 in the first shooting area 13 and the maximum brightness value among multiple brightness values ​​output by pixel 10 in the reference shooting area 14. Therefore, the reflectance R can be calculated accurately.

[0111] Furthermore, the image processing device 6 determines the physical properties of the object E based on the reflectance R and the spectrophotometric reflectance curve (spectral reflectance data) representing the spectrophotometric reflectance of multiple substances. Thus, the physical properties of the object E can be accurately determined.

[0112] Furthermore, the image processing device 6 determines the physical properties of the object E by comparing the reflectance R with a threshold set based on the spectrophotometric reflectance curve. Thus, even if the calculated reflectance R deviates from the material corresponding to the spectrophotometric reflectance curve, the physical properties of the object E can still be determined.

[0113] Furthermore, the image processing device 6 corrects the image of the object E by dividing the brightness value of each image corresponding to the pixel 10 of the first shooting area 13 by the reflectance R. As a result, the brightness value of the image corresponding to the pixel 10 of the first shooting area 13 is corrected to the same level as the brightness value of the image corresponding to the pixel 10 of the reference shooting area 14, thus enabling the acquisition of a clear image of the object E.

[0114] (Second Implementation)

[0115] (Regarding the structure of the imaging element)

[0116] Figure 15 This is a top view showing the structure of the imaging element according to the second embodiment.

[0117] exist Figure 15 The imaging element 11 consists of m elements in the X direction and n elements in the Y direction (in... Figure 15 The pixel array 15 consists of 508×508 pixels 10 arranged in a grid pattern.

[0118] Pixel array 15 includes pixels 10 allocated to the first shooting area 13, pixels 10 allocated to the second shooting area 16, pixels 10 allocated to the third shooting area 17, and pixels 10 allocated to the reference shooting area 14. Figure 15 In the image (Xi, Yj), pixels 10 where i is odd and j is odd are assigned to the first shooting area 13. Furthermore, pixels 10 where i is odd and j is even are assigned to the second shooting area 16. Pixels 10 where i is even and j is odd are assigned to the third shooting area 17. Pixels 10 where i is even and j is even are assigned to the reference shooting area 14.

[0119] Optical interference filters that allow light of the first, second, and third wavelength bands to pass through are respectively provided on the pixels 10 of the first, second, and third imaging regions 13, 16, and 17. That is, the first, second, and third imaging regions 13, 16, and 17 are areas where pixels 10 are respectively configured to capture the spectral images of the first, second, and third wavelength bands. In this embodiment, the first wavelength band is set to the red band (625–780 nm), the second wavelength band to the green band (500–565 nm), and the third wavelength band to the blue band (450–485 nm).

[0120] The reference imaging area 14 is an area configured with pixels 10 for capturing images of a reference band including the first, second, and third bands. In this embodiment, the reference band is set to 400–800 nm. Furthermore, the reference band does not necessarily need to include the entire first, second, and third bands; it only needs to include a portion of each band. That is, the reference band only needs to overlap with the first, second, and third bands.

[0121] (Regarding the operation of the image processing device)

[0122] Reference Figures 16-19The inspection method for the object to be inspected according to the second embodiment will be described. In the inspection method according to the second embodiment, Figure 4 The material property determination process (step S5) and the image correction process (step S6) are different. These processes will be explained below. In addition, in the image extraction process, let's say that as the extracted image p4, the image contained in the region of image (x4, y2) to image (x11, y8) is extracted; as the extracted image p5, the image contained in the region of image (x12, y8) to image (x22, y14) is extracted; and as the extracted image p6, the image contained in the region of image (x14, y2) to image (x11, y8) is extracted.

[0123] (Regarding the handling of physical property determination)

[0124] Reference Figures 16-19 The physical property determination process (step S5) of the image processing device 6 will be explained. Figure 16 This is a diagram showing an example of an image of sheet S captured by the imaging element according to the second embodiment. Figure 17 This is a diagram showing an example of the brightness value of the sheet S captured by the imaging element according to the second embodiment. Figure 18 This is a flowchart illustrating the process of determining the physical properties of the image processing apparatus according to the second embodiment.

[0125] If the image processing device 6 acquires the extracted image p (in) Figure 16 In step S31, images p4 to p6 are extracted. Then, among the images contained in the extracted images p, the image δ that corresponds to the pixel 10 of the reference shooting area 14 and has the highest feature quantity is extracted (step S32).

[0126] The image processing device 6 extracts the image α that corresponds to the pixel 10 of the first shooting area 13 and has the highest feature quantity from the images adjacent to the extracted image δ (step S33).

[0127] The image processing device 6 extracts the image β that corresponds to the pixel 10 of the second shooting area 16 and has the highest feature quantity from the images adjacent to the extracted image δ (step S34).

[0128] The image processing device 6 extracts the image γ that corresponds to the pixel 10 of the third shooting area 17 and has the highest feature quantity from the images adjacent to the extracted image δ (step S35).

[0129] For example, in Figure 16In the extracted image p4, image (X6, Y4) (image δ4) corresponds to image δ, which has the highest feature quantity and corresponds to pixel 10 of the reference shooting region 14. Furthermore, image (X7, Y5) (image α4) corresponds to image δ4, which has the highest feature quantity and corresponds to pixel 10 of the first shooting region 13. Furthermore, image (X7, Y4) (image β4) corresponds to image δ4, which has the highest feature quantity and corresponds to pixel 10 of the second shooting region 16. Furthermore, image (X6, Y5) (image γ4) corresponds to image δ4, which has the highest feature quantity and corresponds to pixel 10 of the third shooting region 17. Details will be omitted, but in extracted image p5, images δ5, α5, β5, and γ5 correspond to images δ, α, β, and γ, respectively. Furthermore, in extracted image p6, images δ6, α6, β6, and γ6 correspond to images δ, α, β, and γ, respectively. In addition, images α, β, and γ were extracted from regions adjacent to the image δ extracted as a specific example, but this is not the only method used.

[0130] After step S35, the reflectances R11 to R13 of the object E in the first, second, and third bands are calculated based on the brightness values ​​of image δ and images α, β, and γ, respectively (step S36). Specifically, reflectance R11 can be calculated by (brightness value of image α) / (brightness value of image δ). Reflectance R12 can be calculated by (brightness value of image β) / (brightness value of image δ). Reflectance R13 can be calculated by (brightness value of image γ) / (brightness value of image δ).

[0131] For example, in Figure 19 In the above, the reflectance of object E1 is R11 = 155 / 255 ≈ 0.60, so the reflectance R11 of object E1 is 60%. The reflectance of object E1 is R12 = 155 / 255 ≈ 0.60, so the reflectance R12 of object E1 is 60%. The reflectance of object E1 is R13 = 140 / 255 ≈ 0.55, so the reflectance R13 of object E1 is 55%. Similarly, the reflectances R11 to R13 of objects E2 and E3 can be calculated separately.

[0132] After step S36, the reflectance is plotted on a graph (step S37). The calculated reflectance R for each band is plotted on a graph with wavelength as the X-axis and reflectance R as the Y-axis. In this embodiment, the reflectance R for each band is plotted using the center value of the band (refer to...). Figure 19 ).

[0133] Will Figure 19 The plotted reflectance and Figure 8The spectrophotometric reflectance curves are compared, and the closest spectrophotometric reflectance curve is selected based on correlation. The physical properties of object E are then determined based on the spectrophotometric reflectance curve (step S38). The plot of the reflectance of object E1 is closest to... Figure 8 The image processing device 6 determines that object E1 is Fe based on the spectroscopic reflectance curve of Fe. Therefore, the image processing device 6 determines that object E1 is Fe. The plot of the reflectance of object E2 is closest to... Figure 8 The reflectance curve of Al is shown in the image. Therefore, the image processing device 6 determines that object E2 is Al. The plot of the reflectance R of object E3 is most approximately equal to... Figure 8 The image processing device 6 determines that the object E3 is Cu based on the spectrophotometric reflectance curve of Cu.

[0134] (Regarding image correction processing)

[0135] If the image processing device 6 acquires the extracted image p (p1 to p3) and the reflectance R11 to R13 (R1 to R3), it corrects the image of the extracted image p.

[0136] The images corresponding to pixels 10 in the first shooting area 13, the second shooting area 16, and the third shooting area 17 have lower brightness values ​​than the images corresponding to pixels 10 in the reference shooting area 14. This is because pixels 10 in the first shooting area 13, the second shooting area 16, and the third shooting area 17 generate spectral images with a narrower wavelength band than the reference band. Therefore, by correcting the brightness value of the image corresponding to pixels 10 in the first shooting area 13 to the same level as the brightness value of the image corresponding to pixels 10 in the reference shooting area 14, a clear image of the object E can be obtained.

[0137] For example, the above correction can be performed by dividing the brightness value of each image corresponding to pixel 10 of the first shooting area 13 by the reflectance R11, dividing the brightness value of each image corresponding to pixel 10 of the second shooting area 16 by the reflectance R12, and dividing the brightness value of each image corresponding to pixel 10 of the third shooting area 17 by the reflectance R13. By performing such correction on the extracted images p1 to p3 before correction, it is possible to generate images such as... Figure 10B , Figure 11B as well as Figure 12B Such a corrected image pw (pw1~pw3).

[0138] (Other implementation methods)

[0139] As described above, the implementation methods have been illustrated as examples of the technology disclosed in this application. However, the technology in this disclosure is not limited to this and can also be applied to implementation methods that have been appropriately modified, substituted, added, omitted, etc.

[0140] Furthermore, although the imaging device 1 and the illumination device 2 are configured as a dark-field optical system in the above embodiment, they could also be configured as a bright-field optical system. Additionally, although the imaging device 1 is configured as a line sensor, it could also be configured as a region sensor. Furthermore, the image processing device 6 can generate both moving images and still images based on the pixel signals output from the imaging element 11.

[0141] Furthermore, in the first embodiment, such as Figure 3 As shown, adjacent pixels 10 are respectively assigned to the first shooting area 13 and the reference shooting area 14, but the allocation of pixels 10 in the first shooting area 13 and the reference shooting area 14 is not limited to this. For example, multiple adjacent pixels 10 (e.g., 2×2 pixels 10) may be respectively assigned to the first shooting area 13 and the reference shooting area 14. Furthermore, a pixel 10 may be assigned to the first shooting area 13, and the pixels 10 surrounding that pixel 10 may be assigned to the reference shooting area 14. That is, the first shooting area 13 and the reference shooting area 14 may not be allocated according to every single pixel 10. Similarly, in the first shooting area 13, the reference shooting area 14, the second shooting area 16, and the third shooting area 17 in the second embodiment, the allocation of pixels 10 is also not limited to this. Figure 15 Examples.

[0142] Furthermore, the configuration of the pixels 10 disposed on the imaging element 11 is not limited to the configuration described above. Furthermore, the number of pixels in the imaging element 11 is not limited to the number described above.

[0143] According to this disclosure, it is possible to determine the physical properties of an object while suppressing the decrease in resolution of the image obtained from the imaging element.

[0144] Industrial availability

[0145] The inspection apparatus disclosed herein can be used to inspect foreign objects, defects, etc. contained in components used in semiconductors, electronic devices, secondary batteries, etc.

Claims

1. An inspection method for detecting objects contained in an inspected body by taking pictures with an inspection device. The inspection device includes an imaging element, which has the following characteristics: The first imaging area includes multiple first pixels, which capture images of the object in the first band and output multiple first feature values; and The reference imaging area includes multiple reference pixels. These reference pixels capture images of the object in a reference band that overlaps with the first band and output multiple reference feature values. The inspection method includes: The reflectance calculation step involves determining the reflectance of the object in the first band, i.e., the first reflectance, based on at least one of the plurality of first characteristic quantities and at least one of the plurality of reference characteristic quantities. The property determination step determines the property of the object based on the first reflectivity; and The image correction step corrects the image of the object generated based on the output from the imaging element, based on at least one of the plurality of first feature quantities and at least one of the plurality of reference feature quantities. At least one of the plurality of first feature quantities is the largest first feature quantity among the plurality of first feature quantities. At least one of the plurality of reference feature quantities is the largest reference feature quantity among the plurality of reference feature quantities. The object being inspected is a solid.

2. The inspection method according to claim 1, wherein, In the property determination step, the property of the object is determined based on the first reflectance and the spectrophotometric reflectance data representing the spectrophotometric reflectance of multiple substances.

3. The inspection method according to claim 2, wherein, In the property determination step, the property of the object is determined by comparing the first reflectance with a threshold set based on the spectral reflectance data.

4. The inspection method according to any one of claims 1 to 3, wherein, In the image correction step, the image of the object is corrected by dividing the plurality of first feature quantities by the first reflectance.

5. The inspection method according to any one of claims 1 to 3, wherein, It also includes a size determination step, which determines the size of the object based on the image of the object that has been corrected in the image correction step.

6. An inspection method for detecting objects contained in an inspected body by taking pictures with an inspection device. The inspection device includes an imaging element, which has the following characteristics: The first imaging area includes multiple first pixels, which capture images of the object in the first band and output multiple first feature values; The second imaging region includes a plurality of second pixels that image the object in a second waveband and output a plurality of second feature quantities. and A reference imaging area includes multiple reference pixels. These reference pixels capture images of the object in reference bands that overlap with the first and second bands, and output multiple reference feature quantities. The inspection method includes: The reflectance calculation step involves determining the reflectance of the object in the first band (i.e., the first reflectance) and the reflectance in the second band (i.e., the second reflectance) based on at least one of the plurality of first characteristic quantities, at least one of the plurality of second characteristic quantities, and at least one of the plurality of reference characteristic quantities. The property determination step determines the property of the object based on the first reflectivity and the second reflectivity. The image correction step corrects the image of the object generated based on the output from the imaging element, based on at least one of the plurality of first features, at least one of the plurality of second features, and at least one of the plurality of reference features; and The size determination step determines the size of the object based on the image of the object that was corrected in the image correction step. At least one of the plurality of first feature quantities is the largest first feature quantity among the plurality of first feature quantities. At least one of the plurality of reference feature quantities is the largest reference feature quantity among the plurality of reference feature quantities. The object being inspected is a solid.

7. The inspection method according to claim 6, wherein, In the property determination step, the property of the object is determined by comparing the first reflectance and the second reflectance with spectrophotometric reflectance data representing the spectrophotometric reflectance of multiple substances.

8. The inspection method according to any one of claims 1 to 3, 6 to 7, wherein, The first characteristic quantity is at least one of the brightness value and luminance of the object captured by the imaging element.

9. An inspection device for detecting objects contained in an inspected body, comprising: Imaging components; and Image processing device The imaging element includes: A first imaging region, comprising multiple first pixels, wherein the multiple first pixels capture an image of the object in a first band and output multiple first feature values; and The reference imaging area includes multiple reference pixels. These reference pixels capture images of the object in a reference band that overlaps with the first band and output multiple reference feature values. The image processing device calculates the reflectance, i.e., the first reflectance, of the object in the first band based on at least one of the plurality of first feature quantities and at least one of the plurality of reference feature quantities. The image processing device determines the physical properties of the object based on the first reflectance. The image processing device corrects the image of the object generated based on the output from the imaging element, based on at least one of the plurality of first feature quantities and at least one of the plurality of reference feature quantities. The image processing device determines the size of the object based on the modified image of the object. At least one of the plurality of first feature quantities is the largest first feature quantity among the plurality of first feature quantities. At least one of the plurality of reference feature quantities is the largest reference feature quantity among the plurality of reference feature quantities. The object being inspected is a solid.

10. An inspection device for detecting objects contained in an inspected body, comprising: Imaging components; and Image processing device The imaging element includes: The first imaging area includes multiple first pixels, which capture images of the object in the first band and output multiple first feature values; A second imaging region, comprising multiple second pixels, wherein the multiple second pixels capture an image of the object in the second band and output multiple second feature values; and A reference imaging area includes multiple reference pixels. These reference pixels capture images of the object in a reference band that overlaps with the first band and the second band, and output multiple reference feature quantities. The image processing device calculates the reflectance of the object in the first band (i.e., the first reflectance) and the reflectance in the second band (i.e., the second reflectance) based on at least one of the plurality of first feature quantities, at least one of the plurality of second feature quantities, and at least one of the plurality of reference feature quantities. The image processing device determines the physical properties of the object based on the first reflectance and the second reflectance. The image processing device corrects the image of the object generated based on the output from the imaging element, based on at least one of the plurality of first features, at least one of the plurality of second features, and at least one of the plurality of reference features. The image processing device determines the size of the object based on the modified image of the object. At least one of the plurality of first feature quantities is the largest first feature quantity among the plurality of first feature quantities. At least one of the plurality of reference feature quantities is the largest reference feature quantity among the plurality of reference feature quantities. The object being inspected is a solid.

Images