Inspection method and inspection device

Abstract

To determine the physical properties of an object while controlling deterioration of the resolution of an image obtained from an imaging device.SOLUTION: Inspection equipment A comprises an imaging device 11 having a first imaging area 13 containing a pixel 10 for capturing an image of an object E in a first wavelength range and a reference imaging area 14 containing a pixel 10 for capturing an image of the object E in a reference wavelength range partially duplicated with the first wavelength range. An image processing system 6 finds a reflectance R of the object E in the first wavelength range based on a first feature quantity that the pixel 10 outputs in the first imaging area 13 and a reference feature quantity that the pixel 10 outputs in the reference imaging area 14, then based on the reflectance R determines the physical properties of the object E. The image processing system 6 compensates an image of the object E that is generated in response to an output from the imaging device 11 based on the first feature quantity and the reference feature quantity.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present disclosure relates to an inspection device and an inspection method for an object to be inspected. [Background technology]

[0002] 2. Description of the Related Art In the field of devices such as semiconductors, electronic devices, and secondary batteries, inspection apparatuses are known that use image sensors to detect objects (such as foreign objects and defects) in objects under inspection.

[0003] In Patent Document 1, spectroscopic images of a plurality of wavelength bands are generated, and features of the spectroscopic images are compared with features of normal data to detect foreign matter (object) mixed in an object to be inspected (test object). That is, in Patent Document 1, the object is detected by utilizing the difference in physical properties between the test object and the object. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2016-138789 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, when using the technology of Patent Document 1, in order to generate spectral images of multiple wavelengths, it is necessary to assign pixels of the image sensor to each wavelength band. Therefore, the spectral images for each wavelength band have a lower resolution than the image obtained from the resolution of the image sensor. This results in a coarse image including the object, which reduces the accuracy of, for example, measuring the size of the object.

[0006] Therefore, an object of the present disclosure is to provide an inspection method and an inspection apparatus that can determine the physical properties of an object while suppressing a decrease in the resolution of an image obtained from an imaging element. [Means for solving the problem]

[0007] In order to achieve the above-mentioned object, an inspection method according to one embodiment of the present disclosure is an inspection method for detecting an object contained in an inspected body by imaging it with an inspection device, the inspection device comprising an imaging element having a first imaging area including pixels that image the object in a first wavelength band and a reference imaging area including pixels that image the object in a reference wavelength band that overlaps with the first wavelength band, and the inspection method includes a reflectance calculation step of calculating a first reflectance, which is the reflectance of the object in the first wavelength band, based on a first feature that is a feature output by a pixel in the first imaging area and a reference feature that is a feature output by a pixel in the reference imaging area, a physical property determination step of determining a physical property of the object based on the first reflectance, and an image correction step of correcting an image of the object generated in accordance with the output from the imaging element, based on the first feature and the reference feature. Effect of the Invention

[0008] According to the present disclosure, it is possible to determine the physical properties of an object while suppressing a decrease in the resolution of an image obtained from an imaging element. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a side view of an inspection device according to a first embodiment. [Diagram 2] FIG. 1 is a plan view of an inspection device according to a first embodiment. [Diagram 3] FIG. 1 is a plan view showing the configuration of an imaging element according to a first embodiment. [Figure 4] 4 is a flowchart illustrating the overall operation of the image processing device according to the first embodiment. [Diagram 5] 3A to 3C are diagrams showing examples of images of a sheet captured by an imaging element according to the first embodiment. [Figure 6] 4 is a diagram showing an example of luminance values ​​of a sheet imaged by the imaging element according to the first embodiment. [Figure 7] 5 is a flowchart illustrating the flow of a physical property determination process of the image processing device according to the first embodiment. [Figure 8] 1 is a graph showing spectral reflectance curves illustrating the spectral reflectance of a number of substances. [Figure 9] 5 is a flowchart illustrating the flow of correction image processing in the image processing device according to the first embodiment. [Figure 10] 11A and 11B are diagrams for comparing an extracted image before correction and a corrected image after correction. [Figure 11] 11A and 11B are diagrams for comparing an extracted image before correction and a corrected image after correction. [Figure 12] 11A and 11B are diagrams for comparing an extracted image before correction and a corrected image after correction. [Figure 13] 5A to 5C are views showing examples of corrected images of a sheet according to the first embodiment. [Figure 14] 3A to 3C are diagrams for explaining a method for determining the size of an object according to the first embodiment. [Figure 15] FIG. 11 is a plan view showing the configuration of an image sensor according to a second embodiment. [Figure 16] 13A and 13B are diagrams showing examples of images of a sheet captured by an imaging element according to the second embodiment. [Figure 17] 13 is a diagram showing an example of luminance values ​​of a sheet imaged by an imaging element according to the second embodiment. FIG. [Figure 18] 10 is a flowchart illustrating the flow of a physical property determination process in an image processing device according to a second embodiment. [Figure 19] FIG. 11 is a graph showing a plot of reflectance according to the second embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, the embodiments of the present invention will be described in detail with reference to the drawings. The following description of the preferred embodiments is merely illustrative in nature and is not intended to limit the present invention, its application, or its uses.

[0011] Fig. 1 shows a side view of the inspection device, and Fig. 2 shows a plan view of the inspection device. As shown in Fig. 1 and Fig. 2, the inspection device A includes an imaging device 1, an illumination device 2, rollers 3 to 5, and an image processing device 6. A conveyor belt 7 is wound around the outer periphery of the rollers 3 to 5.

[0012] The inspection device A inspects a sheet S (object to be inspected). The sheet S is used in the device field such as semiconductors, electronic devices, and secondary batteries. In the following explanation, the object to be inspected is a sheet-like object, but the object to be inspected does not have to be a sheet-like object. In addition, when the sheet S is a long object, the sheet S is wound around rollers 3-4 instead of the conveyor belt 7. The sheet S is then conveyed in the direction of the arrow D by the rollers 3-5.

[0013] The inspection device A detects an object E, such as a defect or foreign object, contained in the sheet S. The defects include not only imperfections or shortages during the production of the sheet S, such as short circuits or disconnections in the inspected sheet S, but also damage to the sheet S (for example, scratches caused by the sheet S coming into contact with other members). If the detected object E is larger than a predetermined size, the inspection device determines that the sheet S contains an object. The sheet S is placed on a conveyor belt 7 and conveyed in the direction of the arrow D indicated by a solid line in FIGS. 1 and 2.

[0014] The imaging device 1 includes an imaging element 11, and captures an image of the sheet S being conveyed by the conveyor belt 7. Here, the imaging device 1 is configured as an area sensor that captures an image of the entire sheet S between rollers 4 and 5. Note that the imaging device 1 may be configured as a line sensor instead of an area sensor.

[0015] The imaging device 1 transmits pixel signals output from the imaging element 11 to the image processing device 6. 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 the X direction and the Y direction is defined as the Z direction.

[0016] The illumination device 2 has a light source composed of, for example, an LED, a laser, a halogen light source, or the like, and irradiates light onto the scanning area (sheet S) of the imaging device 1 between the rollers 4 and 5. Specifically, the illumination device 2 is installed so that the direction of light irradiation is such that the incident angle with respect to the conveyor belt 7 is about 10°. In addition, the imaging device 1 and the illumination device 2 are composed of a dark field optical system so that the light irradiated by the illumination device 2 does not directly enter the imaging element 11. The imaging device 1 and the illumination device 2 may be composed of a bright field optical system, but it is preferable to be composed of a dark field optical system. By configuring it as a dark field optical system, it is possible to apply light to the object E at a low angle, so that the background of the object E does not shine (the brightness of the background (ground level) where there is no foreign object becomes low gradation). As a result, the brightness of the object E becomes higher than that of the background, and the SN (signal to noise (brightness of foreign object / brightness of background)) ratio increases, making it possible to generate a clear image of the object E.

[0017] The roller 3 is rotated by a drive mechanism (not shown) to drive the conveyor belt 7 and convey the sheet S in the direction of the solid arrow in the drawing.

[0018] The image processing device 6 is, for example, a computer. The image processing device 6 determines the physical properties and size of the object E based on the pixel signal received from the imaging device 1 (imaging element 11). Specifically, the image processing device 6 executes an image extraction process, a physical property determination process, an image correction process, and a size determination process, which will be described later.

[0019] The configuration of the inspection device A is not limited to the above configuration.

[0020] Furthermore, the inspection device A may be provided with a rotary encoder that detects the rotation speed of the rollers 3 to 5. In this case, the amount of movement of the sheet S conveyed by the conveyor belt 7 may be detected based on the detection result of the rotary encoder.

[0021] Furthermore, the image of the sheet S may be captured while the sheet S or the imaging device 1 is moving, or may be captured while the sheet S or the imaging device 1 is stationary.

[0022] (First embodiment) (About the configuration of the image sensor) 3 is a plan view showing the configuration of the image sensor according to the first embodiment. The image sensor 11 is, for example, a CMOS (Complementary MOS) sensor.

[0023] 3, the image sensor 11 is configured with a pixel array 12 in which m pixels 10 in the X direction and n pixels 10 in the Y direction (508×508 in FIG. 3) are arranged in a lattice pattern. In the following description, the i-th pixel 10 in the X direction and the j-th pixel 10 in the Y direction may be referred to as pixel (Xi, Yj).

[0024] The pixel array 12 includes pixels 10 allocated to the first imaging region 13 and pixels 10 allocated to the reference imaging region 14. In Fig. 3, among the pixels (Xi, Yj), the pixels 10 with i being an odd number and j being an even number, and the pixels 10 with i being an even number and j being an odd number, are allocated to the first imaging region 13. Also, among the pixels (Xi, Yj), the pixels 10 with i being an odd number and j being an odd number, and the pixels 10 with i being an even number and j being an even number, are allocated to the reference imaging region 14. That is, in Fig. 3, the pixels 10 allocated to the first imaging region 13 and the reference imaging region 14 are arranged adjacent to each other.

[0025] An optical interference filter that transmits light in a first wavelength band is placed on the pixels 10 of the first imaging region 13. That is, the first imaging region 13 is a region in which the pixels 10 that capture a spectral image in the first wavelength band are arranged. In this embodiment, the first wavelength band is a red wavelength band (625 to 780 nm).

[0026] The reference imaging region 14 is a region in which the pixels 10 that capture an image of a reference wavelength band including the first wavelength band are arranged. In this embodiment, the reference wavelength band is 400 to 800 nm. The reference wavelength band does not necessarily have to include the entire range of the first wavelength band, but may include a part of the wavelength band. For example, when the first wavelength band is 625 to 780 nm, the reference wavelength band may be 400 to 700 nm. In other words, the reference wavelength band may overlap with the first wavelength band.

[0027] (About the operation of image processing device) The inspection method for an object to be inspected according to the first embodiment will be described with reference to Fig. 4 to Fig. 14. Fig. 4 is a flowchart illustrating the overall operation flow of the image processing device according to the first embodiment.

[0028] The imaging device 1 (imaging element 11) captures an image of the sheet S conveyed by the conveyor belt 7 between the rollers 4 and 5. The image processing device 6 acquires (receives) a pixel signal output from the imaging device 1 (step S1).

[0029] Based on the pixel signal acquired from the imaging device 110, the image processing device 6 generates an image P of the sheet S (step S2). Then, the image processing device 6 executes an image extraction process, which will be described later, to generate an extracted image p (step S3).

[0030] The image processing device 6 determines whether or not the image P includes an extracted image p of the object E (step S4). When the image processing device 6 determines that the image P does not include the extracted image p of the object E (No in step S4), the image processing device 6 ends the process. In other words, the image processing device 6 determines that the sheet S does not include the object E.

[0031] When it is determined that the image P includes an image of the object E (Yes in step S4), the image processing device 6 executes a physical property determination process (step S5) to be described later, and determines the physical properties of the object E.

[0032] After step S5, the image processing device 6 executes an image correction process (step S6) to generate a corrected image pw by correcting 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).

[0033] (About image extraction processing) Next, the image extraction process of the image processing device 6 will be described with reference to Fig. 5 and Fig. 6. Fig. 5 is a diagram showing an example of an image of a sheet captured by the imaging element according to the first embodiment. Fig. 6 is a diagram showing an example of the luminance value of a sheet captured by the imaging element according to the first embodiment.

[0034] In step S2, the image processing device 6 generates an image P of the sheet S shown in Fig. 5 based on the pixel signal acquired from the imaging element 11. In Fig. 5, it is assumed that the sheet S is photographed so as to fit within the dashed line portion. In the following description, image data corresponding to pixel (Xi, Yj) is referred to as image (xi, yi).

[0035] Then, in step S3, the image processing device 6 executes an image extraction process. Specifically, the image processing device 6 extracts an extracted image p of the object E based on the feature amount of each image (xi, yj) in the image P. Examples of the feature amount include the luminance value and brightness of each image (xi, yj) in the image P. The feature amount may be determined based on the feature amount of the sheet S that does not include the object E. The presence or absence of the object E is determined using feature amounts such as the area value, size in the X direction, size in the Y direction, shape, and total density of the object E. In this embodiment, a case where the feature amount is the luminance value of each image (xi, yj) in the image P will be described as an example.

[0036] Figure 6 shows the luminance value for each image (xi, yj) in image P. In Figure 6, the luminance value is displayed in 256 gradations of 8 bits, with the minimum luminance value being 0 and the maximum luminance value being 255. In Figure 6, when no object E exists on sheet S (ground level), the luminance value is 0.

[0037] First, the image processing device 6 extracts an image (xi, yj) whose brightness value is equal to or greater than a threshold value. Then, the image processing device 6 regards adjacent images (xi, yj) among the extracted images as one object E. Here, "adjacent images" refers to images adjacent to one image in the X direction (horizontal direction), Y direction (vertical direction), X direction and Y direction (diagonal direction). Specifically, for image (xi, yj), images (xi, yj±1), (xi±1, yj) and (xi±1, yj±1) are adjacent images. The image processing device 6 generates an extracted image p so as to include the extracted object E.

[0038] For example, in FIG. 6, when the brightness threshold is set to 20, the image processing device 6 extracts the area of ​​the image (xi, yj) surrounded by the dashed line as the objects E1 to E3. Then, the image processing device 6 generates extracted images p1 to p3 so as to include the objects E1 to E3, respectively (see FIG. 5 and FIG. 6). Specifically, an image included in the area of ​​the image (x4, y2) to the image (x11, y8) is extracted as the extracted image p1. An image included in the area of ​​the image (x14, y2) to the image (x20, y6) is extracted as the extracted image p2. An image included in the area of ​​the image (x12, y8) to the image (x22, y14) is extracted as the extracted image p3.

[0039] It should be noted that, when the image processing device 6 generates the extracted image p from the image P in step S4, it determines that the image P includes the extracted image p of the object E.

[0040] (About physical property determination processing) Next, the physical property determination process (step S5) of the image processing device 6 will be described with reference to Fig. 5 to Fig. 8. Fig. 7 is a flowchart illustrating the flow of the physical property determination process of the image processing device according to the first embodiment.

[0041] When the image processing device 6 acquires an extraction image p (extraction images p1 to p3 in Figs. 5 and 6) (step S11), it extracts an image δ having the highest feature amount among the images included in the extraction image p, which corresponds to the pixel 10 in the reference imaging region 14 (step S12). Then, the image processing device 6 extracts an image α having the highest feature amount among the images adjacent to the extracted image δ, which corresponds to the pixel 10 in the first imaging region 13 (step S13). The "adjacent images" here refer to images adjacent to one image in the X direction (horizontal direction), Y direction (vertical direction), and X and Y directions (diagonal directions).

[0042] 6, in extracted images p1 to p3, images δ1 to δ3 (brightness values ​​255, 255, 255) correspond to image δ, respectively, and images α1 to α3 (brightness values ​​155, 230, 204) correspond to image α, respectively.

[0043] After step S13, the reflectance R of the object E in the first wavelength band is calculated based on the feature values ​​(brightness values) of the images δ and α (step S14). Specifically, the reflectance R can be calculated by (brightness value of image α) / (brightness value of image δ). The pixel 10 in the first imaging region 13 corresponding to the image α captures a spectral image in the first wavelength band, and the pixel 10 in the reference imaging region 14 corresponding to the image δ captures a spectral image in a reference wavelength band including the first wavelength band. Therefore, the reflectance R of the object E in the first wavelength band can be calculated by comparing the brightness values ​​(feature values) of the images α and δ.

[0044] 9, the reflectance R1 of the object E1 is 155 / 255 ≈ 0.60, and the reflectance R1 of the object E1 is 60%. The reflectance R2 of the object E2 is 235 / 255 ≈ 0.90, and the reflectance R2 of the object E2 is 90%. The reflectance R3 of the object E3 is 204 / 255 ≈ 0.80, and the reflectance R3 of the object E3 is 80%.

[0045] 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 set based on a spectral reflectance curve (spectral reflectance data, see FIG. 8) indicating the spectral reflectance of a plurality of substances. The image processing device 6 compares the reflectance R with the threshold to determine the physical properties of the object E.

[0046] FIG. 8 shows the spectral reflectance curves of Al, Fe, and Cu in each wavelength band. Since the first wavelength band is 625 to 780 nm, if the reflectance is 50% to 70%, the object E can be determined to be Fe, if the reflectance is 70% to 90%, the object E can be determined to be Cu, and if the reflectance is 90% or more, the object E can be determined to be Al. Specifically, since the reflectance R1 of the object E1 is 60%, the object E1 is determined to be Fe. Since the reflectance R2 of the object E2 is 90%, the object E2 is determined to be Al. Since the reflectance R2 of the object E3 is 80%, the object E2 is determined to be Fe. In this way, the physical properties of the object E can be determined by setting a threshold value for determining the physical properties of the object E based on the spectral reflectance curve.

[0047] The method of calculating the reflectance R is not limited to the above-mentioned method. For example, the reflectance R can be calculated by the following method.

[0048] First, an image of the object E is extracted from the extraction image p. At this time, an image is extracted excluding one pixel around the object E. This makes it possible to extract the object E present in the entire area of ​​the extraction image p.

[0049] Next, among the extracted images of the object E, an average luminance value α' is calculated by averaging the luminance values ​​of the images corresponding to the pixels 10 in the first imaging region 13. In addition, among the extracted images of the object E, an average luminance value δ' is calculated by averaging the luminance values ​​of the images corresponding to the pixels 10 in the reference imaging region 14. Then, based on the average luminance value α' and the average luminance value δ', the reflectance R of the object E in the first wavelength band is calculated. Specifically, the reflectance R is calculated by (average luminance value α') / (average luminance value δ'). In this way, by averaging the luminance values ​​used in calculating the reflectance, it is possible to reduce errors in the reflectance due to the influence of singular points.

[0050] It is possible to detect materials other than metal as the object E. For example, it is also possible to measure resin. The reflectance of resin is low in the visible light region and high in the infrared region. Therefore, when detecting resin, it is necessary to widen the first wavelength band and the reference wavelength band to 1000 nm for measurement.

[0051] (Image correction processing) Next, the correction image processing (step S6) of the image processing device 6 will be described with reference to Fig. 9 to Fig. 13. Fig. 9 is a flowchart illustrating the flow of the correction image processing of the image processing device according to the first embodiment.

[0052] When the image processing device 6 acquires the extraction images p (p1 to p3) and the reflectances R (R1 to R3) (step S21), it corrects the extraction images p (step S22). Then, the image processing device 6 generates corrected images pw by correcting the extraction images p (step S23).

[0053] 10 to 12 are diagrams for comparing extracted images before correction with corrected images after correction. Specifically, Fig. 10(a) to Fig. 12(a) show extracted images p1 to p3 before correction and their brightness values, respectively, and Fig. 10(b) to Fig. 12(b) show corrected images pw1 to pw3 after correction and their brightness values, respectively.

[0054] 10(a) to 12(a), the image corresponding to the pixel 10 in the first imaging region 13 has a lower luminance value than the image corresponding to the pixel 10 in the reference imaging region 14. This is because the pixel 10 in the first imaging region 13 generates a spectral image in a first wavelength band that is narrower than the reference wavelength band. Therefore, by correcting the luminance value of the image corresponding to the pixel 10 in the first imaging region 13 to be approximately the same as the luminance value of the image corresponding to the pixel 10 in the reference imaging region 14, a clear image of the object E can be acquired.

[0055] For example, the above correction can be performed by dividing the luminance value of each image corresponding to the pixel 10 in the first imaging region 13 by the reflectance R. By performing such correction on the extracted images p1 to p3 before correction, it is possible to generate corrected images pw (pw1 to pw3) as shown in Figures 10(b) to 12(b). By replacing the corrected image pw with the position of the extracted image p in image P, a clear image PW of the object E is obtained as shown in Figure 13.

[0056] The correction process in step S22 is not limited to the above-mentioned method. For example, the luminance value of the image corresponding to the pixel 10 in the first imaging region 13 may be set to the average value of the luminance values ​​that are equal to or greater than a threshold value among the images corresponding to the pixel 10 in the reference imaging region 14 adjacent to the image.

[0057] For example, in FIG. 5 and FIG. 10, when correcting an image (X6, Y3), the average value of the luminance values ​​of the adjacent images (X6, Y2), (X5, Y3), (X7, Y3), and (X6, Y4) becomes the luminance value of the image (X6, Y3). Since the luminance value of the image (X6, Y2) is 0, it is excluded from the averaging. Here, the luminance value of the image (X6, Y3)=(50+255+255) / 3≈187. In this way, the luminance value of the image corresponding to the pixel 10 in the first imaging region 13 may be corrected based on the luminance value of the image corresponding to the pixel 10 in the reference imaging region 14.

[0058] (Regarding determining the size of an object) Next, the size determination process (step S7) of the image processing device 6 will be described with reference to Fig. 14. Fig. 14 is a diagram for explaining the object size determination method according to the first embodiment. Specifically, Figs. 14(a) to (c) respectively show corrected images pw1' to pw3' obtained by performing binarization process on the corrected images pw1 to pw3 of Figs. 10(b) to 12(b) with a luminance value of 30 as a threshold value.

[0059] The size of the object E may be, for example, the area, maximum length, aspect ratio, vertical width, horizontal width, Feret diameter (maximum value, minimum value, etc.), or the length of the main axis (maximum value, minimum value, etc.). In this embodiment, a case where the maximum Feret diameter F is calculated as the size of the object E will be described as an example. The Feret diameter means the vertical and horizontal lengths of a rectangle circumscribing a certain object, and the maximum Feret diameter indicates the maximum length of the rectangle circumscribing the object.

[0060] 14(a) to (c), the lengths indicated by the arrows are the maximum Feret's diameters of the objects E1 to E3, and the sizes of the objects E1 to E3 can be determined.

[0061] As described above, the inspection device A includes an imaging element 11 having a first imaging region 13 including pixels 10 that capture an image of the object E in a first wavelength band, and a reference imaging region 14 including pixels 10 that capture an image of the object E in a reference wavelength band that overlaps with the first wavelength band. The image processing device 6 obtains a reflectance R (first reflectance) of the object E in the first wavelength band based on a luminance value (first feature amount) output by the pixel 10 in the first imaging region 13 and a luminance value (reference feature amount) output by the pixel 10 in the reference imaging region 14, 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 according to the output from the imaging element 11 based on the reflectance R. That is, the reflectance R of the object E in the first wavelength band is obtained based on a luminance value output by the pixel 10 in the first imaging region 13 and a luminance value output by the pixel 10 in the reference imaging region 14, so that the physical properties of the object E can be determined. In addition, since the image output from the imaging element 11 is corrected by the determined reflectance R, it is possible to suppress a decrease in the resolution of the image obtained from the imaging element. Therefore, it is possible to determine the physical properties of the object while suppressing a decrease in the resolution of the image obtained from the imaging element.

[0062] Moreover, the reflectance R is calculated based on the maximum luminance value among the luminance values ​​output by the pixels 10 in the first imaging region 13 and the maximum luminance value among the luminance values ​​output by the pixels 10 in the reference imaging region 14. This allows the reflectance R to be calculated accurately.

[0063] Furthermore, the image processing device 6 determines the physical properties of the object E based on the reflectance R and a spectral reflectance curve (spectral reflectance data) indicating the spectral reflectances of a plurality of substances. This allows the physical properties of the object E to be determined accurately.

[0064] Furthermore, the image processing device 6 compares the reflectance R with a threshold value set based on the spectral reflectance curve to determine the physical properties of the object E. This makes it possible to determine the physical properties of the object E even if there is a discrepancy between the determined reflectance R and the corresponding substance on the spectral reflectance curve.

[0065] Furthermore, the image processing device 6 corrects the image of the object E by dividing the luminance value of each image corresponding to the pixel 10 in the first imaging region 13 by the reflectance R. This corrects the luminance value of the image corresponding to the pixel 10 in the first imaging region 13 to be approximately the same as the luminance value of the image corresponding to the pixel 10 in the reference imaging region 14, making it possible to acquire a clear image of the object E.

[0066] Second embodiment (About the configuration of the image sensor) FIG. 15 is a plan view showing the configuration of the imaging element according to the second embodiment.

[0067] The imaging element 11 in FIG. 15 is configured with a pixel array 15 in which m pixels 10 in the X direction and n pixels 10 in the Y direction (508×508 in FIG. 18) are arranged in a lattice pattern.

[0068] The pixel array 15 includes pixels 10 assigned to the first imaging region 13, pixels 10 assigned to the second imaging region 16, pixels 10 assigned to the third imaging region 17, and pixels 10 assigned to the reference imaging region 14. In FIG. 15, pixels 10 with i being an odd number and j being an odd number among the pixels (Xi, Yj) are assigned to the first imaging region 13. Also, pixels 10 with i being an odd number and j being an even number among the pixels (Xi, Yj) are assigned to the second imaging region 16. Pixels 10 with i being an even number and j being an odd number among the pixels (Xi, Yj) are assigned to the third imaging region 17. Pixels 10 with i being an even number and j being an even number among the pixels (Xi, Yj) are assigned to the reference imaging region 14.

[0069] Optical interference filters that transmit light in the first, second, and third wavelength bands are respectively installed on the pixels 10 of the first imaging region 13, the second imaging region 16, and the third imaging region 17. That is, the first imaging region 13, the second imaging region 16, and the third imaging region 17 are regions in which the pixels 10 that capture spectral images in the first, second, and third wavelength bands are respectively arranged. In this embodiment, the first wavelength band is a red wavelength band (625 to 780 nm), the second wavelength band is a green wavelength band (500 to 565 nm), and the third wavelength band is a blue wavelength band (450 to 485 nm).

[0070] The reference imaging region 14 is a region in which the pixels 10 are arranged to capture an image of a reference wavelength band including a first wavelength band, a second wavelength band, and a third wavelength band. In this embodiment, the reference wavelength band is 400 to 800 nm. The reference wavelength band does not necessarily include the entire range of the first wavelength band, the second wavelength band, and the third wavelength band, but may include a part of each of the wavelength bands. In other words, the reference wavelength band may overlap with the first wavelength band, the second wavelength band, and the third wavelength band.

[0071] (About the operation of image processing device) With reference to Figs. 16 to 19, an inspection method for an object to be inspected according to the second embodiment will be described. The inspection method according to the second embodiment differs from Fig. 3 in the property determination process (step S5) and the image correction process (step S6). These processes will be described below. In the image extraction process, it is assumed that an image included in the region of images (x4, y2) to (x11, y8) is extracted as extracted image p4, an image included in the region of images (x14, y2) to (x11, y8) is extracted as extracted image p5, and an image included in the region of images (x12, y8) to (x22, y14) is extracted as extracted image p6.

[0072] (About physical property determination processing) The physical property determination process (step S5) of the image processing device 6 will be described with reference to Figs. 16 to 19. Fig. 16 is a diagram showing an example of an image of the sheet S imaged by the imaging element according to the second embodiment. Fig. 17 is a diagram showing an example of the luminance value of the sheet S imaged by the imaging element according to the second embodiment. Fig. 18 is a flowchart for explaining the flow of the physical property determination process of the image processing device according to the second embodiment.

[0073] When the image processing device 6 acquires an extraction image p (in FIG. 16, extraction images p4 to p6) (step S31), it extracts an image δ that corresponds to pixel 10 in the reference imaging area 14 and has the highest feature amount from among the images included in the extraction image p (step S32).

[0074] The image processing device 6 extracts image α, which corresponds to pixel 10 in the first imaging region 13 and has the highest feature amount, from among images adjacent to the extracted image δ (step S33).

[0075] The image processing device 6 extracts an image β that corresponds to the pixel 10 in the second imaging region 16 and has the highest feature amount from among the images adjacent to the extracted image δ (step S34).

[0076] The image processing device 6 extracts image γ, which corresponds to pixel 10 in the third imaging region 17 and has the highest feature amount, from among images adjacent to the extracted image δ (step S35).

[0077] For example, in the extracted image p4 in FIG. 16, the image (X6, Y4) (image δ4) corresponds to the pixel 10 of the reference imaging region 14 and corresponds to the image δ with the highest feature amount. In addition, the image (X7, Y5) (image α4) corresponds to the pixel 10 of the first imaging region 13 among the images adjacent to the image δ4 and corresponds to the pixel with the highest feature amount. In addition, the image (X7, Y4) (image β4) corresponds to the pixel 10 of the second imaging region 16 among the images adjacent to the image δ4 and corresponds to the pixel with the highest feature amount. In addition, the image (X6, Y5) (image γ4) corresponds to the pixel 10 of the third imaging region 17 among the images adjacent to the image δ4 and corresponds to the pixel with the highest feature amount. Although a detailed description is omitted, in the extracted image p5, the images δ5, α5, β5, and γ5 correspond to the images δ, α, β, and γ, respectively. In the extracted image p6, the images δ6, α6, β6, and γ6 correspond to the images δ, α, β, and γ, respectively. Note that, as a specific example, the images α, β, and γ are extracted from the region adjacent to the extracted image δ, but this is not limiting.

[0078] After step S35, reflectances R11 to R13 of the object E in the first wavelength band, the second wavelength band, and the third wavelength band are calculated based on the brightness values ​​of image δ and images α, β, and γ (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).

[0079] For example, in Fig. 19, the reflectance R11 of the object E1 is 155 / 255 ≒ 0.60, and the reflectance R11 of the object E1 is 60%. The reflectance R12 of the object E1 is 155 / 255 ≒ 0.60, and the reflectance R12 of the object E1 is 60%. The reflectance R13 of the object E1 is 140 / 255 ≒ 0.55, and the reflectance R13 of the object E1 is 55%. Similarly, the reflectances R11 to R13 can be calculated for the objects E2 and E3, respectively.

[0080] After step S36, the reflectance is plotted on a graph (step S37). The calculated reflectance R in each wavelength band is plotted on a graph with the wavelength on the X-axis and the reflectance R on the Y-axis. In this embodiment, the reflectance R in each wavelength band is plotted at the median value of the wavelength band (see FIG. 19).

[0081] The plotted reflectance in FIG. 19 is compared with the spectral reflectance curve in FIG. 8, the closest spectral reflectance curve is selected based on the correlation, and the physical properties of object E are determined based on the spectral reflectance curve (step S38). The plot of reflectance of object E1 is most approximate to the spectral reflectance curve of Fe in FIG. 8. Therefore, the image processing device 6 determines that object E1 is Fe. The plot of reflectance of object E2 is most approximate to the spectral reflectance curve of Al in FIG. 8. Therefore, the image processing device 6 determines that object E2 is Al. The plot of reflectance R of object E3 is most approximate to the spectral reflectance curve of Cu in FIG. 8. Therefore, the image processing device 6 determines that object E3 is Cu.

[0082] (About image correction processing) Upon acquiring the extraction image p (p1 to p3) and the reflectances R11 to R13 (R1 to R3), the image processing device 6 corrects the image of the extraction image p.

[0083] The images corresponding to the pixels 10 in the first imaging region 13, the second imaging region 16, and the third imaging region 17 have lower luminance values ​​than the images corresponding to the pixels 10 in the reference imaging region 14. This is because the pixels 10 in the first imaging region 13, the second imaging region 16, and the third imaging region 17 generate spectral images in a wavelength band narrower than the reference wavelength band. Therefore, by correcting the luminance value of the images corresponding to the pixels 10 in the first imaging region 13 to be approximately the same as the luminance value of the images corresponding to the pixels 10 in the reference imaging region 14, a clear image of the object E can be acquired.

[0084] For example, the above correction can be performed by dividing the luminance value of each image corresponding to pixel 10 in the first imaging region 13 by the reflectance R11, dividing the luminance value of each image corresponding to pixel 10 in the second imaging region 16 by the reflectance R12, and dividing the luminance value of each image corresponding to pixel 10 in the third imaging region 17 by the reflectance R13. By performing such correction on extracted images p1 to p3 before correction, corrected images pw (pw1 to pw3) such as those shown in Figures 12(b) to 14(b) can be generated.

[0085] (Other embodiments) As described above, the embodiments have been described as examples of the technology disclosed in the present application. However, the technology in the present disclosure is not limited to these, and may be applied to embodiments in which modifications, substitutions, additions, omissions, etc. are made as appropriate.

[0086] In the above embodiment, the imaging device 1 and the illumination device 2 are configured as a dark field optical system, but may be configured as a bright field optical system. The imaging device 1 is configured as a line sensor, but may be configured as an area sensor. The image processing device 6 may generate a moving image or a still image from the pixel signal output from the imaging element 11.

[0087] In the first embodiment, as shown in FIG. 3, adjacent pixels 10 are assigned to the first imaging region 13 and the reference imaging region 14, respectively, but the assignment of pixels 10 to the first imaging region 13 and the reference imaging region 14 is not limited to this. For example, adjacent pixels 10 (for example, 2×2 pixels 10) may be assigned to the first imaging region 13 and the reference imaging region 14, respectively. Also, one pixel 10 may be assigned to the first imaging region 13, and the pixels 10 around this pixel 10 may be assigned to the reference imaging region 14. That is, the first imaging region 13 and the reference imaging region 14 may not be assigned to each pixel 10. Note that, in the second embodiment, the assignment of pixels 10 to the first imaging region 13, the reference imaging region 14, the second imaging region 16, and the third imaging region 17 is not limited to the example of FIG. 15.

[0088] The arrangement of the pixels 10 arranged in the imaging element 11 is not limited to the arrangement described above. The number of pixels in the imaging element 11 is not limited to the number described above. [Industrial Applicability]

[0089] The inspection device of the present disclosure can be used to inspect for foreign matter and defects contained in components used in semiconductors, electronic devices, secondary batteries, and the like. [Explanation of symbols]

[0090] A Inspection equipment 1. Imaging device 6 Image Processing Device 10 pixels 11 Image sensor 13 First imaging area 14 Reference imaging area 16 Second imaging area 17 Third imaging area E(E1~E3) Object P Image p Extracted image pw corrected image

Claims

1. 1. An inspection method for detecting an object contained in an object to be inspected by imaging the object with an inspection device, comprising: The inspection device includes: a first imaging region including pixels for capturing an image of the object in a first wavelength band; a reference imaging area including pixels that capture an image of the object in a reference wavelength band that overlaps with the first wavelength band; an imaging element having a reflectance calculation step of calculating a first reflectance, which is a reflectance of the object in the first wavelength band, based on a first feature amount, which is a feature amount output by a pixel in the first imaging region, and a reference feature amount, which is a feature amount output by a pixel in the reference imaging region; a physical property determination step of determining a physical property of the object based on the first reflectance; an image correction step of correcting an image of the object generated in accordance with an output from the imaging element, based on the first feature amount and the reference feature amount; 4. A method for testing comprising:

2. 2. The inspection method according to claim 1, an inspection method, wherein the first reflectance is calculated based on the first feature amount that is the maximum among the first feature amounts and the reference feature amount that is the maximum among the reference feature amounts.

3. 3. The inspection method according to claim 1, In the physical property determining step, the physical property of the object is determined based on the first reflectance and spectral reflectance data indicating spectral reflectances of a plurality of substances.

4. 4. The inspection method according to claim 3, The inspection method, wherein in the physical property determining step, the physical property of the object is determined by comparing the first reflectance with a threshold value set based on the spectral reflectance data.

5. The inspection method according to any one of claims 1 to 4, An inspection method, wherein in the image correcting step, the image of the object is corrected by dividing the first feature amount by the first reflectance.

6. The inspection method according to any one of claims 1 to 5, The inspection method further includes a size determination step of determining a size of the object from the image of the object corrected in the image correction step.

7. 1. An inspection method for detecting an object contained in an object to be inspected by imaging the object with an inspection device, comprising: The inspection device includes: a first imaging region including pixels for capturing an image of the object in a first wavelength band; a second imaging region including pixels for capturing an image of the object in a second wavelength band; a reference imaging area including pixels that capture an image of the object in a reference wavelength band that overlaps with the first wavelength band and the second wavelength band; an imaging element having a reflectance calculation step of calculating a first reflectance, which is a reflectance in the first wavelength band, and a second reflectance, which is a reflectance in the second wavelength band, of the object based on a first feature amount, which is a feature amount output by a pixel in the first imaging area, a second feature amount, which is a feature amount output by a pixel in the second imaging area, and a reference feature amount, which is a feature amount output by a pixel in the reference imaging area; a physical property determination step of determining a physical property of the object based on the first reflectance and the second reflectance; an image correction step of correcting an image of the object generated in response to an output from the imaging element, based on the first feature amount, the second feature amount, and the reference feature amount; a size determination step of determining a size of the object from the image of the object corrected in the image correction step; 4. A method for testing comprising:

8. 8. The inspection method according to claim 7, An inspection method, wherein in the physical property determining step, the physical property of the object is determined by comparing the first reflectance and the second reflectance with spectral reflectance data indicating the spectral reflectances of a plurality of substances.

9. The inspection method according to any one of claims 1 to 8, An inspection method, wherein the feature amount is at least one of a luminance value and a brightness value of the object imaged by the imaging element.

10. An inspection device for detecting an object contained in an object to be inspected, An imaging element; Image processing device Equipped with The imaging element includes: a first imaging region including pixels for capturing an image of the object in a first wavelength band; a reference imaging area including pixels that capture an image of the object in a reference wavelength band that overlaps with the first wavelength band; Equipped with The image processing device includes: calculating a first reflectance of the object in the first wavelength band based on a first feature amount that is a feature amount output by a pixel in the first imaging region and a reference feature amount that is a feature amount output by a pixel in the reference imaging region; determining a physical property of the object based on the first reflectance; correcting an image of the object generated in accordance with an output from the imaging element based on the first feature amount and the reference feature amount; The inspection apparatus determines a size of the object from the corrected image of the object.

11. An inspection device for detecting an object contained in an object to be inspected, An imaging element; Image processing device Equipped with The imaging element includes: a first imaging region including pixels for capturing an image of the object in a first wavelength band; a second imaging region including pixels for capturing an image of the object in a second wavelength band; a reference imaging area including pixels that capture an image of the object in a reference wavelength band that overlaps with the first wavelength band and the second wavelength band; Equipped with The image processing device includes: determining a first reflectance of the object, which is a reflectance in the first wavelength band, and a second reflectance of the object, which is a reflectance in the second wavelength band, based on a first feature amount that is a feature amount output by a pixel in the first imaging region, a second feature amount that is a feature amount output by a pixel in the second imaging region, and a reference feature amount that is a feature amount output by a pixel in the reference imaging region; determining a physical property of the object based on the first reflectance and the second reflectance; correcting an image of the object generated in accordance with an output from the imaging element, based on the first feature amount, the second feature amount, and the reference feature amount; The inspection apparatus determines a size of the object from the corrected image of the object.

Images