Inspection method and inspection apparatus

Abstract

The present application provides an inspection method and an inspection device. The inspection device (A) according to the present embodiment includes an illumination device capable of irradiating a first light of a first wavelength band and a reference light of a reference wavelength band having an overlap with the first wavelength band, a camera device that captures an object to be inspected and outputs a pixel signal, and an image processing device. The illumination device irradiates the first light and the reference light to the object to be inspected at different timings within one capturing time. The image processing device calculates a first reflectance, which is a reflectance in the first wavelength band of the object, based on the pixel signal, and determines a physical property of the object based on the first reflectance.

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 taking an image with an inspection device. The inspection device includes an illumination device capable of illuminating a first light in a first band and a reference light in a reference band overlapping with the first band, an imaging device for photographing the inspected object and outputting pixel signals, and an image processing device. The inspection method includes: the illumination device illuminating the inspected object with the first light and the reference light at different timings within an imaging time; the image processing device calculating the reflectivity, i.e., the first reflectivity, of the object in the first band based on the pixel signals; and the image processing device determining the physical properties of the object based on the first reflectivity.

[0008] Another embodiment of this disclosure relates to an inspection method for detecting objects contained in an inspected object by taking an image with an inspection device. The inspection device includes an illumination device capable of illuminating a first light of a first band, a second light of a second band, and a reference light of a reference band overlapping the first and second bands; an imaging device for photographing the inspected object and outputting pixel signals; and an image processing device. The inspection method includes: the illumination device illuminating the inspected object with the first light, the second light, and the reference light at different timings within an imaging period; the image processing device calculating 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 the pixel signals; and the image processing device determining the physical properties of the object based on the first and second reflectances.

[0009] One embodiment of this disclosure relates to an inspection apparatus that detects objects contained in an inspected body by taking pictures. It includes an illumination device capable of illuminating a first light in a first band and a reference light in a reference band overlapping with the first band, an imaging device for photographing the inspected body and outputting pixel signals, and an image processing device. The illumination device illuminates the inspected body with the first light and the reference light at different timings within an imaging period. The image processing device calculates the reflectivity, i.e., the first reflectivity, in the first band of the object based on the pixel signals, and determines the physical properties of the object based on the first reflectivity. Attached Figure Description

[0010] Figure 1 This is a side view of the inspection device according to the first embodiment.

[0011] Figure 2 This is a top view of the inspection device according to the first embodiment.

[0012] Figure 3 This is a top view showing the structure of the imaging element according to the first embodiment.

[0013] Figure 4 This is a timing diagram showing the shooting timing of the shooting device and the illumination timing of the lighting device in the inspection apparatus according to the first embodiment.

[0014] Figure 5 This is a flowchart illustrating the overall operation of the image processing apparatus according to the first embodiment.

[0015] Figure 6 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 7 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 8 This is a flowchart illustrating the process of determining the physical properties of the image processing apparatus according to the first embodiment.

[0018] Figure 9 It is a graph showing the spectrophotometric reflectance curves representing the spectrophotometric reflectance of multiple substances.

[0019] Figure 10A This is a diagram used to explain the method for determining the size of an object according to the first embodiment.

[0020] Figure 10B This is a diagram used to explain the method for determining the size of an object according to the first embodiment.

[0021] Figure 10C This is a diagram used to explain the method for determining the size of an object according to the first embodiment.

[0022] Figure 11 This is a timing diagram showing the shooting timing of the shooting device and the illumination timing of the lighting device in the inspection apparatus according to the second embodiment.

[0023] Figure 12 This is a diagram showing an example of an image of a sheet captured by the imaging element according to the second embodiment.

[0024] Figure 13 This is a diagram showing an example of an image of a sheet captured by the imaging element according to the second embodiment.

[0025] Figure 14A This is a diagram illustrating an example of extracting the brightness value of an image according to the second embodiment.

[0026] Figure 14B This is a diagram illustrating an example of extracting the brightness value of an image according to the second embodiment.

[0027] Figure 14C This is a diagram illustrating an example of extracting the brightness value of an image according to the second embodiment.

[0028] Figure 14D This is a diagram illustrating an example of extracting the brightness value of an image according to the second embodiment.

[0029] Figure 14E This is a diagram illustrating an example of extracting the brightness value of an image according to the second embodiment.

[0030] Figure 14FThis is a diagram illustrating an example of extracting the brightness value of an image according to the second embodiment.

[0031] Figure 15G This is a diagram illustrating an example of extracting the brightness value of an image according to the second embodiment.

[0032] Figure 15H This is a diagram illustrating an example of extracting the brightness value of an image according to the second embodiment.

[0033] Figure 15I This is a diagram illustrating an example of extracting the brightness value of an image according to the second embodiment.

[0034] Figure 15J This is a diagram illustrating an example of extracting the brightness value of an image according to the second embodiment.

[0035] Figure 15K This is a diagram illustrating an example of extracting the brightness value of an image according to the second embodiment.

[0036] Figure 16 This is a flowchart illustrating the grouping process of the image processing apparatus according to the second embodiment.

[0037] Figure 17A This is a diagram used to illustrate the generation process of the original extracted image involved in the second embodiment.

[0038] Figure 17B This is a diagram used to illustrate the generation process of the original extracted image involved in the second embodiment.

[0039] Figure 17C This is a diagram used to illustrate the generation process of the original extracted image involved in the second embodiment.

[0040] Figure 18 This is a flowchart illustrating the process of determining the physical properties of the image processing apparatus according to the second embodiment.

[0041] Figure 19 It is a graph showing a chart of reflectivity according to the second embodiment.

[0042] Symbol Explanation

[0043] A. Inspection device;

[0044] 1. Filming device;

[0045] 6. Image processing device;

[0046] 11. Imaging components;

[0047] E(E1~E6, E11~E21) refers to the object;

[0048] R represents reflectivity;

[0049] P-image;

[0050] Extract images using p(p1~p6, p11~p21, p16a~p16c). Detailed Implementation

[0051] When using the technology in Patent Document 1 to generate multiple spectral images from a single sensor element, the subject to be inspected needs to be photographed for each wavelength band, thus increasing the imaging time. In particular, the imaging time increases as the number of spectral images generated increases.

[0052] 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 increase in shooting time.

[0053] Hereinafter, embodiments of the present invention 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 invention, its applications, or its uses.

[0054] 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 photographing device 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.

[0055] 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 3-4 instead of conveyor belt 7. Then, sheet S is conveyed by rollers 3-5 in the direction of arrow D.

[0056] 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.

[0057] 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.

[0058] 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.

[0059] The illumination device 2, for example, has a light source composed of LEDs, lasers, halogen light sources, etc., and 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 signal-to-noise ratio (the brightness of the foreign object / the brightness of the substrate) is improved, thus enabling the generation of a clear image of the object E. Details will be described later, but the illumination device 2 can illuminate multiple wavelengths of light.

[0060] 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.

[0061] 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.

[0062] Furthermore, the structure of the inspection device A is not limited to the structure described above.

[0063] 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.

[0064] (First Embodiment)

[0065] (Regarding the structure of the imaging element)

[0066] 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.

[0067] 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).

[0068] (Regarding the operation of the filming and lighting equipment)

[0069] First, the operation of the shooting device and lighting device when shooting film S (the object being examined) will be explained. Figure 4 This is a timing diagram showing the shooting timing of the imaging device and the illumination timing of the illumination device in the inspection apparatus according to the first embodiment. In this embodiment, the shooting timing of the imaging device 1 and the illumination timing of the illumination device 2 are set based on encoder pulses. Regarding... Figure 4 The encoder pulse, for example, is 1 μm, but is not limited to this.

[0070] Furthermore, in this embodiment, the illumination device 2 can illuminate both the first band and the reference band. For example, the first band is a red band (625–780 nm), and the reference band is 400–800 nm. Moreover, the reference band does not necessarily need to encompass 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 could also be 400–700 nm. That is, the reference band only needs to overlap with the first band.

[0071] like Figure 4As shown, during one frame, exposure of pixel 10 (image sensor 11), readout of pixel signals, and illumination based on illumination device 2 are performed. When the image sensor 1 is a region sensor, the readout interval of the pixel signals is set to be below the frame rate. Furthermore, when the image sensor 1 is a line sensor, the readout interval of the pixel signals is set to be below the minimum scan rate. In this embodiment, the image sensor 1 is a region image sensor with a frame rate of 240fps (4.17 mes / time), and the sheet S feed speed is 2500mm / sec or less. That is, pixel signals are read out every 12500 encoder pulses, i.e., every 12.5mm. In this case, the maximum speed at which the image sensor 1 can normally capture images is 12.5mm ÷ (1 / 240) (sec) = 3000mm / sec; if the feed speed is below this, the image sensor 1 operates normally.

[0072] Furthermore, within one exposure time, the illumination device 2 illuminates two different wavelengths (here, the first wavelength and the reference wavelength) at different timings. Specifically, the illumination device 2 illuminates the reference wavelength after a given pulse (e.g., 0 to 100 pulses) from the start of exposure. The illumination time at this time is 2 to 5 μsec. Additionally, the illumination device 2 illuminates the first wavelength after a given pulse (e.g., 2500 pulses) from the start of exposure. The illumination time at this time is 3 μsec. Since the illumination device 2 illuminates both the first wavelength and the reference wavelength within one exposure time, a switching time between the illuminated wavelengths is required. Therefore, the exposure time is set longer than the illumination time and switching time of the illumination device 2, for example, set to 3.9 msec.

[0073] (Regarding the operation of the image processing device)

[0074] Reference Figures 5 to 10C The inspection method for the subject according to the first embodiment will be described.

[0075] Figure 5 This is a flowchart illustrating the overall operation of the image processing apparatus according to the first embodiment.

[0076] As described above, the imaging device 1 (imaging element 11) takes a picture of the sheet S (the object to be inspected) conveyed by the conveyor belt 7 between rollers 4 and 5. At this time, according to... Figure 4 The timing diagram is used to photograph the sheet S. The image processing device 6 acquires (receives) the pixel signal output from the imaging device 1 (step S1).

[0077] The image processing apparatus 6 generates an image P based on the pixel signals acquired from the imaging device 1 (step S2). Then, the image processing apparatus 6 performs the image extraction processing described later to generate an extracted image p from the image P (step S3).

[0078] The image processing device 6 determines whether the image P contains the extracted image p of the object E (step S4). If the image processing device 6 determines that the image P does not contain the extracted image p of the object E ("No" in step S4), the processing ends. That is, the image processing device 6 determines that the sheet S does not contain the object E.

[0079] If the image processing device 6 determines that the image P contains an image 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. Then, the image processing device 6 uses the generated modified image pw to determine the size of the object E (step S6).

[0080] (Regarding image extraction and processing)

[0081] Next, refer to Figure 6 as well as Figure 7 The image extraction and processing of the image processing device 6 will be explained. Figure 6 This is a diagram showing an example of an image of a sheet captured by the imaging element according to the first embodiment. Figure 7 This is a diagram showing an example of the brightness value of a sheet captured by the imaging element according to the first embodiment.

[0082] In step S2, the image processing device 6 generates image P based on the pixel signals acquired from the imaging element 11. Image P includes images P1 to Pi (not shown). The sheet S is photographed multiple times (i times in this case) between rollers 4 and 5, therefore image P includes images P1 to Pi. In the following description, the image captured the i-th time will be designated as image Pi.

[0083] In this embodiment, the illumination time of the lighting device 2 is sufficiently small compared to the conveying speed of rollers 4 and 5, so the captured image does not elongate in the Y direction. When the illumination time is sufficiently large compared to the conveying speed, the image Pi elongates in the Y direction. For example, if the object E is captured at a resolution of 25 μm, a conveying speed of 2500 mm / sec, and an illumination time of 10 μsec, it becomes 2500 (mm / sec) × 10 μsec = 25 μm, which is approximately 2 pixels longer in the Y direction.

[0084] Furthermore, to prevent missing object E, the image acquisition interval is set by establishing repeating regions P1' between images. Specifically, as follows... Figure 6 as well as Figure 7 As shown, a repeating region P1' is set between images P1 and P2. Figure 6 as well as Figure 7In this example, the width of the repeating region P1' in the Y direction is set to approximately 16 Pix (0.4 mm). Furthermore, the setting of this repeating region can be arbitrarily configured.

[0085] 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.

[0086] Figure 7 The brightness values ​​for each image (xi, yj) in image P are shown. Figure 7 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 7 In the case where there is no object E (groundlevel) in the sheet S, the brightness value becomes 0.

[0087] 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 an extracted image p that includes the extracted object E.

[0088] For example, in Figure 7 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 solid lines into images containing objects E1 to E6. Then, the image processing unit 6 generates extracted images p1 to p6 (refer to...) in a manner that each contains objects E1 to E6. Figure 6 as well as Figure 7Specifically, as image p1, the image contained in the region from image (x3, y1) to image (x9, y7) is extracted. As image p2, the image contained in the region from image (x10, y1) to image (x16, y5) is extracted. As image p3, the image contained in the region from image (x18, y1) to image (x22, y5) is extracted. As image p4, the image contained in the region from image (x3, y101) to image (x9, y107) is extracted. As image p5, the image contained in the region from image (x10, y101) to image (x16, y105) is extracted. As image p6, the image contained in the region from image (x18, y101) to image (x22, y105) is extracted.

[0089] In addition, if the image processing device 6 generates an extracted image p from the image P in step S4, it determines that the image P contains the extracted image p of the object E.

[0090] (Regarding the handling of physical property determination)

[0091] Below, refer to Figures 6-9 The physical property determination process (step S5) of the image processing device 6 will be explained. Figure 8 This is a flowchart illustrating the process of determining the physical properties of the image processing apparatus according to the first embodiment.

[0092] If the image processing device 6 acquires the extracted image p (in) Figure 6 as well as Figure 7 In step S11, images p1 to p6 are extracted, and then the extracted images p are grouped (step S12). Specifically, the image processing device 6 classifies the extracted images p with the same X coordinate into the same group. For example, in Figure 6 as well as Figure 7 In the process, extracted images p1 and p4 were classified into the same group, extracted images p2 and p5 were classified into the same group, and extracted images p3 and p6 were classified into the same group.

[0093] As described above, the illumination device 2 illuminates two different wavelengths (here, the first wavelength and the reference wavelength) at different timings within one exposure time. Therefore, in image P, two extracted images p are generated for one object E. Furthermore, in this embodiment, the first wavelength is illuminated after the reference wavelength. That is, the two extracted images p generated for one object E are included in image P with a shift in the Y direction. Therefore, extracted images p with the same X coordinate become images representing the same object E. By classifying extracted images p with the same X coordinate into the same group, it is possible to determine that extracted images p belonging to the same group are images representing the same object E. That is, in this embodiment, it is possible to determine that objects E1 and E4 are the same object, objects E2 and E5 are the same object, and objects E3 and E6 are the same object.

[0094] Furthermore, in this embodiment, after illuminating the reference band light, the first band light is then illuminating the image. Therefore, it can be determined that within the same group, the extracted image p(p1 to p3) with the smaller Y coordinate is the extracted image generated by illuminating the reference band light, and the extracted image p(p4 to p6) with the larger Y coordinate is the extracted image generated by illuminating the first band light.

[0095] After step S12, among the extracted images p belonging to the same group, the image δ with the highest feature quantity among the images contained in the extracted image p with the smaller Y coordinate is extracted (step S13).

[0096] Then, the image processing device 6 extracts the image α with the highest feature quantity among the images contained in the extracted image p that belongs to the same group (step S14).

[0097] exist Figure 7 In the extracted images p1 to p3, images δ1 to δ3 (brightness values ​​of 255, 255, 255) are respectively equivalent to image δ, and images α1 to α3 (brightness values ​​of 155, 230, 204) are respectively equivalent to image α.

[0098] Following step S14, 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 S15). Specifically, the reflectance R can be calculated by (brightness value of image α) / (brightness value of image δ). Image α is a spectroscopic image of the first band, and image δ is a spectroscopic image of a reference band including 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.

[0099] For example, in Figure 7In the above, the reflectance of object E1 (E4) is R1 = 155 / 255 ≈ 0.60, making its reflectance R1 60%. The reflectance of object E2 (E5) is R2 = 230 / 255 ≈ 0.90, making its reflectance R2 90%. The reflectance of object E3 (E6) is R3 = 204 / 255 = 0.80, making its reflectance R3 80%.

[0100] After step S14, the image processing device 6 determines the physical properties of the object E based on the calculated reflectance R (step S16). 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 9 The image processing device 6 compares the reflectance R with a threshold to determine the physical properties of the object E.

[0101] exist Figure 9 The 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 (E4) has a reflectance R1 of 60%, therefore object E1 is determined to be Fe. Object E2 (E5) has a reflectance R2 of 90%, therefore object E2 is determined to be Al. Object E3 (E6) 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.

[0102] 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. The following explanation will take the case of calculating the reflectance of object E1 (E4) as an example.

[0103] First, the image of object E1 is extracted from the extracted image p1. Then, the image excluding the surrounding 1 pixel of object E1 is extracted. Thus, object E1, which exists throughout the entire area of ​​the extracted image p1, can be extracted. Furthermore, similarly to the extracted image p1, the image of object E4 is extracted from the extracted image p4.

[0104] Next, in the image of object E1 extracted from image p1, the average brightness value δ' is calculated by averaging the brightness values ​​of the image. Furthermore, in the image of object E4 extracted from image p4, the average brightness value α' is calculated by averaging the brightness values ​​of the image. Then, the reflectance R of object E1 (E4) 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, the error in reflectance caused by singularities can be reduced.

[0105] Furthermore, the target object E can also detect substances other than metals. For example, it can also detect resins. Resins have low reflectivity in the visible light region and high reflectivity in the infrared region. Therefore, when detecting resins, it is necessary to extend the first band and the reference band to 1000 nm for detection.

[0106] (Regarding the determination of the size of an object)

[0107] Next, refer to Figures 10A to 10C The size determination process (step S6) of the image processing device 6 will be explained. Figures 10A to 10C This diagram is used to explain the method for determining the size of an object according to the first embodiment. Specifically, Figures 10A to 10C The corrected images pw1 to pw3 are shown respectively, obtained by binarizing the extracted images p1 to p3 with a brightness value of 30 as a threshold. These extracted images p1 to p3 are images of object E (E1 to E3) generated from the reference band. Compared with the extracted images based on the first band, the extracted images based on the reference band have higher feature quantities (brightness), thus enabling accurate determination of the size of object E. Alternatively, the size can also be determined using the images of object E (E1 to E3) generated from the first band, i.e., the extracted images p1 to p3.

[0108] 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.

[0109] exist Figures 10A to 10C 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.

[0110] Alternatively, the extracted images p1 to p3 can be used directly to determine the dimensions of objects E1 to E3 without binarizing them.

[0111] As explained above, the inspection apparatus A according to this embodiment includes an illumination device 2 capable of illuminating a first light in a first band and a reference light in a reference band overlapping with the first band, an imaging device 1 capable of imaging a sheet S (the object to be inspected) and outputting pixel signals, and an image processing device 6. The illumination device 2 illuminates the sheet S with the first light and the reference light at different timings within one imaging time. The image processing device 6 calculates the reflectance, i.e., the first reflectance R, in the first band of the object E based on the pixel signals, and determines the physical properties of the object E based on the first reflectance R. That is, the illumination device 2 illuminates the sheet S with the first light and the reference light at different timings within one imaging time, thereby forming an extracted image p of the object E based on the first light and an extracted image p of the object E based on the reference light in one image. Since the first reflectance R of the object E in the first band can be calculated based on these two extracted images p, the physical properties of the object E can be determined. Furthermore, since a single image contains both the extracted image p of the object E based on the first light and the extracted image p of the object E based on the reference light, it is not necessary to photograph the sheet S according to each wavelength, thus suppressing the increase in shooting time. Therefore, it is possible to determine the physical properties of the object E while suppressing the increase in shooting time.

[0112] Furthermore, the feature quantity extracted from image p is the brightness value or lightness of object E. Therefore, the physical properties of object E can be determined based on its brightness value or lightness.

[0113] Furthermore, the image processing device 6 uses the extracted image p of the object E based on the reference band to determine the size of the object E. This allows the determination of the size of the object E.

[0114] (Second Implementation)

[0115] The second embodiment differs from the first embodiment in the structure of the lighting device 2 and the operation of the imaging device and image control device. Furthermore, in the second embodiment, the same symbols are used for structures identical to those in the first embodiment, and their descriptions are omitted.

[0116] (Regarding the operation of the filming and lighting equipment)

[0117] In the second embodiment, the illumination device 2 is capable of illuminating light in the first to third wavebands and a reference waveband. The first waveband is a red waveband (625–780 nm), the second waveband is a green waveband (500–565 nm), the third waveband is a blue waveband (450–485 nm), and the reference waveband is 400–800 nm. Furthermore, the reference waveband does not necessarily need to include the entire first waveband; it only needs to include a portion of it. For example, if the first waveband is 625–780 nm, the reference waveband could also be 400–700 nm. Moreover, the reference waveband does not necessarily need to include the entire first, second, and third wavebands; it only needs to include a portion of each. That is, the reference waveband only needs to overlap with the first, second, and third wavebands.

[0118] Figure 11 This is a timing diagram showing the shooting timing of the imaging device and the illumination timing of the illumination device in the inspection apparatus according to the second embodiment. Figure 11 As shown, exposure of the imaging element 11, readout of pixel signals, and illumination based on the lighting device 2 are performed during 1 frame.

[0119] Illumination device 2 illuminates four different wavelengths (here, wavelengths 1 to 3 and a reference wavelength) at different timings within one exposure time. Specifically, illumination device 2 illuminates the reference wavelength after a given pulse (e.g., 0 pulses) from the start of exposure. The illumination time at this time is 2 to 5 μsec. Furthermore, illumination device 2 illuminates the first wavelength after a given pulse (e.g., 500 pulses) from the start of exposure. The illumination time at this time is 3 μsec. Furthermore, illumination device 2 illuminates the second wavelength after a given pulse (e.g., 1500 pulses) from the start of exposure. The illumination time at this time is 3 μsec. Furthermore, illumination device 2 illuminates the third wavelength after a given pulse (e.g., 3000 pulses) from the start of exposure. The illumination time at this time is 3 μsec.

[0120] That is, by illuminating the first to third bands and the reference band with light at different timings, the image position of an object E can be made different in the Y direction. Specifically, the images of the object E illuminated by the first to third bands of light are formed at positions offset in the Y direction by 500μm, 1500μm, and 3000μm (hereinafter sometimes referred to as the first to third offset values) respectively, based on the image of the object E illuminated by the reference band of light.

[0121] (Regarding image extraction and processing)

[0122] Figure 12 as well as Figure 13 This is a diagram showing an example of an image of a sheet captured by the imaging element according to the second embodiment. Figures 14A to 14F as well as Figures 15G to 15K This is a diagram illustrating an example of extracting the brightness values ​​of an image according to the second embodiment. Additionally, Figure 12 This shows the region of image P from (x0, y0) to (x507, y59). Figure 13 The region of image P from image (x0, y60) to image (x507, y180) is shown. Figures 14A to 14F as well as Figures 15G to 15K Show each Figure 12 as well as Figure 13 The extracted images are p11 to p21. Furthermore, the objects shown in the extracted images p11 to p21 are respectively designated as objects E11 to E21.

[0123] As described above, illumination device 2 illuminates light in bands 1 to 3 and the reference band at different timings within one exposure time. Therefore, four extracted images (the number of objects × 4) are generated in image P. However, in... Figures 12-15K Only 11 extracted images were generated. This is believed to be because the two objects E are located on the same X-coordinate, resulting in different images of object E (in...). Figure 12 The extracted image (p16) will overlap. Therefore, in this embodiment, by performing... Figure 16 The grouping process shown in the image extraction (object) enables the extraction of all objects E without omission.

[0124] In this embodiment, Figure 8 Execute in step S12 Figure 16 Grouping processing. Figure 16 This is a flowchart illustrating the grouping process involved in the second embodiment.

[0125] First, the image processing device 6 binarizes the extracted images p11 to p21 using a given feature quantity as a threshold (e.g., 20), extracts objects E11 to E21 from each extracted image, and registers the extracted objects in a list (step S401). The feature quantities at this time can include brightness values, object positions, Fretter diameters, etc. In this embodiment, the case where the feature quantity is brightness value will be used as an example for explanation.

[0126] Next, the image processing device 6 extracts the object Ea with the smallest Y coordinate from the objects E registered in the list (step S402). Then, using the X and Y coordinates of object Ea as a reference, the image processing device 6 determines whether object Eb exists at the position of the first offset value in the positive direction of the Y axis (step S403). The first offset value refers to the distance caused by the timing deviation between the light of the reference wavelength band and the light of the first wavelength band irradiated by the illumination device 2.

[0127] If the image processing device 6 determines that an object Eb exists at the position of the first offset value ("Yes" in step S403), it extracts the object Eb (step S404a). Conversely, if the image processing device 6 determines that an object Eb does not exist at the position of the first offset value ("No" in step S403), it reads the initial list and, based on the X and Y coordinates of the object Ea, extracts the object Eb that exists at the position of the first offset value in the positive direction of the Y-axis (step S404b). Although details will be described later, the extracted object is removed from the list. Therefore, in cases of object overlap (e.g., ...), ... Figure 12 In the case of object E16, sometimes the object has been deleted from the list. Here, in order to retrieve object E without omitting it, let's say we retrieve object Eb from the initial list. Furthermore, in the processes described below for steps S406b and S408b, the processing is performed in roughly the same way as in step S404b for the same reason.

[0128] After steps S404a and S404b, the image processing device 6, using the X and Y coordinates of object Ea as a reference, determines whether object Ec exists at a position with a second offset value in the positive direction of the Y-axis (step S405). The second offset value refers to the distance caused by the timing deviation between the light of the reference wavelength band and the light of the second wavelength band irradiated by the illumination device 2. If the image processing device 6 determines that object Ec exists at the position with the second offset value ("Yes" in step S405), it extracts object Ec (step S406a). On the other hand, if the image processing device 6 determines that object Ec does not exist at the position with the second offset value ("No" in step S405), it reads the initial list and, using the X and Y coordinates of object Ea as a reference, extracts object Ec that exists at the position with the second offset value in the positive direction of the Y-axis (step S406b).

[0129] After steps S406a and S406b, the image processing device 6 determines, based on the X and Y coordinates of object Ea, whether object Ed exists at the third offset position (step S407). The third offset value refers to the distance caused by the timing deviation between the light of the reference band and the light of the third band irradiated by the illumination device 2. If the image processing device 6 determines that object Ed exists at the third offset position ("Yes" in step S407), it extracts object Ed (step S408a). On the other hand, if the image processing device 6 determines that object Ed does not exist at the third offset position ("No" in step S407), it reads the initial list and extracts object Ed that exists at the third offset position in the positive direction of the Y-axis, based on the X and Y coordinates of object Ea (step S408b).

[0130] After steps S408a and S408b, the image processing device 6 classifies the extracted objects Ea to Ed into the same group (step S409). Then, the image processing device 6 removes the extracted objects Ea to Ed from the list (step S410).

[0131] After step S410, the image processing device 6 determines whether any objects remain in the list (step S411). If the image processing device 6 determines that objects remain in the list ("Yes" in step S411), it returns to step S402 to perform grouping processing again. If the image processing device 6 determines that no objects remain in the list ("No" in step S411), it ends the processing. That is, the image processing device 6 performs grouping processing until all objects are classified. Through this grouping, objects E classified into the same group become objects representing the same object E.

[0132] Furthermore, in step S404b, the initial list is read out. Based on the X and Y coordinates of object Ea, if object Eb is not present at the first offset value in the positive Y-axis direction, it is assumed that object Ea was not generated by light illuminating a reference wavelength band, but rather by light illuminating any of the first to third wavelength bands. In this case, the image processing device 6 extracts objects from the initial list at offset values ​​1 to 3 in the negative Y-axis direction, based on the X and Y coordinates of object Ea. The extracted object is then used as object Ea, and the processing from step S403 onwards is performed again. As described above, the first to third offset values ​​are set to different values. Therefore, only one true object Ea is extracted.

[0133] For example, in Figure 12 as well as Figure 13In the initial grouping process, objects E11 to E21 are registered in the initial list. After the first grouping process, objects E15, E16, E18, and E20 are grouped into the same group. Next, after the second grouping process, objects E11 to E14 are grouped into the same group. Then, in the third grouping process, object E17 is identified as object Ea. At this point, the remaining objects E19 and E21 in the list do not exist at the first offset value in the positive Y-axis direction relative to object E17. Therefore, the image processing device 6 cannot extract object Eb. Therefore, the image processing device 6 extracts object Eb at the first to third offset values ​​in the negative Y-axis direction, using object E17 as a reference. At this point, object E16 exists at the first offset value in the negative Y-axis direction relative to object E17, so the image processing device 6 identifies object E16 as the true object Ea. Therefore, the image processing device 6 treats object E16 as object Ea and performs the processing after step S403, classifying objects E16, E17, E19, and E21 into the same group.

[0134] Here, regarding the objects E (extracted image p) classified into the same group, since the illumination device 2 illuminates the objects in the order of reference band and bands 1 to 3, it can be determined that: the extracted image p with the smallest Y-coordinate is the extracted image generated by illuminating the reference band (hereinafter referred to as the "reference image"), the extracted image p with the second smallest Y-coordinate is the extracted image generated by illuminating the band 1 (hereinafter referred to as the "first image"), the extracted image p with the third smallest Y-coordinate is the extracted image generated by illuminating the band 2 (hereinafter referred to as the "second image"), and the extracted image p with the largest Y-coordinate is the extracted image generated by illuminating the band 3 (hereinafter referred to as the "third image"). For example, in Figures 12-15K In the diagram, the reference images are extracted images p11, p15, and p16; the first image is extracted images p12, p16, and p17; the second image is extracted images p13, p18, and p19; and the third image is extracted images p14, p20, and p21.

[0135] The following section explains the process of generating the original extracted image.

[0136] In the grouping process described above, when an object E is classified into multiple groups, the extracted images p of overlapping objects E are grouped. In this case, based on the extracted images p of overlapping objects E, it is impossible to determine the reflectivity R of object E, and thus impossible to accurately determine the physical properties of object E. Therefore, the image processing device 6 performs the process of generating the original extracted images p of object E. Figure 8 In step S13 and subsequent processing, the extracted image p generated by the processing is used.

[0137] In one of the processes for generating the original extracted image, for example, when the reference image overlaps with other extracted images p, the original reference image can be generated by synthesizing images 1 through 3 belonging to the same group. For example, in Figures 14A to 14F In this process, the extracted image p11 can be generated by synthesizing the extracted images p12 to p14.

[0138] Furthermore, if any of the extracted images from images 1 to 3 overlaps with other extracted images p, the extracted image can be generated by subtracting the extracted images from images 1 to 3 that do not overlap with other extracted images p from the reference image. For example, in Figures 14A to 14F In this process, the extracted image p12 can be generated by subtracting the feature values ​​of the extracted images p13 and p14 from the feature values ​​of the extracted image p11.

[0139] Furthermore, if any of the extracted images from the 1st to the 3rd extracted images overlaps with other extracted images p, the extracted image can be generated based on the calculable reflectance of the object E. Although details will be described later, among the extracted images p belonging to the same group, the image with the largest feature value among the reference images is designated as image δ, the image with the largest feature value among the 1st images is designated as image α, the image with the largest feature value among the 2nd images is designated as image β, and the image with the largest feature value among the 3rd images is designated as image γ. In this case, the reflectance R of the object E in the 1st band is (brightness value of image α) / (brightness value of image δ). The reflectance R of the object E in the 2nd band is (brightness value of image β) / (brightness value of image δ). The reflectance R of the object E in the 3rd band is (brightness value of image β) / (brightness value of image δ).

[0140] For example, in Figures 12-15K In the extracted image p16, the images of the two objects E overlap. Therefore, the extracted image p16 cannot be used as the first image of object E15.

[0141] Here, as Figures 14A to 14F as well as Figures 15G to 15K As shown, based on the extracted images p15 and p18 (the second image), the reflectance R22 of object E15 (E18, E20) in the second band is 150 / 255≈0.59, therefore the reflectance R22 is 59%. Based on the extracted images p15 and p20 (the third image), the reflectance R23 of object E15 in the third band is 204 / 255≈0.8, therefore the reflectance R23 is 80%. Here, if we refer to... Figure 9Based on the spectrophotometric reflectance curve, object E15 can be identified as Cu. Therefore, the reflectance R21 of object E15 in band 1 can be determined to be approximately 50%. By multiplying this reflectance R23 by the feature value (brightness value) of the extracted image p15, the extracted image p16a of object E15 in band 1 can be generated (refer to...). Figure 17A ).

[0142] Furthermore, by subtracting the estimated extracted image p16a from the extracted image p16, a reference image of the object E17 can be generated. However, in this image generation method, such as Figure 17B As shown, the brightness value in the central part of the image is higher than that in the peripheral part, making it impossible to accurately estimate the extracted image p16b. This is believed to be because, in extracted image p16, the two objects E16 and E17 overlap, resulting in a maximum brightness value exceeding 255. Therefore, using extracted image p18, which belongs to the same group as object E17 and does not overlap, a reference image for object E17 can be estimated. Specifically, by multiplying the maximum magnification of extracted images p16b and p18 (image a2 / image a1 = 150 / 110) by the entire image of extracted image p18, an extracted image p16c of object E17 in the reference band can be generated (see reference). Figure 17C ).

[0143] (Regarding the handling of physical property determination)

[0144] Reference Figure 18 The physical property determination process (step S5) of the image processing apparatus 6 according to the second embodiment will be described. Figure 18 This is a flowchart illustrating the process of determining the physical properties of the image processing apparatus according to the second embodiment.

[0145] If the image processing device 6 acquires the extracted image p (in) Figure 18 In step S31, the extracted images p11 to p21 and the estimated extracted images are extracted. Then, among the extracted images p belonging to the same group, the image δ with the highest feature quantity among the images contained in the reference image (the extracted image p with the smallest Y coordinate) is extracted (step S32).

[0146] The image processing device 6 extracts the image α with the highest feature value among the images contained in the first image (the second smallest extracted image in Y coordinate) from the extracted images p belonging to the same group (step S33).

[0147] Image processing device 6 extracts the image β with the highest feature value from the images contained in the second image (the third smallest extracted image in Y coordinate) among the extracted images p belonging to the same group (step S34).

[0148] The image processing device 6 extracts the image γ with the highest feature value from the images contained in the third image (the image p with the largest Y coordinate) belonging to the same group of extracted images p (step S35).

[0149] For example, in Figure 18 In the extraction process, images p11 to p14 were classified into the same group. Figure 18 In the extracted images p11 to p14, the extracted image δ4 of image p11 is equivalent to image δ, the extracted image α4 of image p12 is equivalent to image α, the extracted image β4 of image p13 is equivalent to image β, and the extracted image γ4 of image p14 is equivalent to image γ.

[0150] Following step S35, the reflectances R31 to R33 of the object E11 (E12 to E14) 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 R31 can be calculated by (brightness value of image α) / (brightness value of image δ). Reflectance R32 can be calculated by (brightness value of image β) / (brightness value of image δ). Reflectance R33 can be calculated by (brightness value of image γ) / (brightness value of image δ).

[0151] For example, in Figure 18 In the above calculations, the reflectance R of object E11 is R31 = 140 / 255 ≈ 0.55, and the reflectance R31 of object E1 is 55%. The reflectance R32 of object E1 is R32 = 155 / 255 ≈ 0.60, and the reflectance R32 of object E11 is 60%. The reflectance R33 of object E11 is R33 = 155 / 255 ≈ 0.60, and the reflectance R33 of object E11 is 60%. Similarly, the reflectance R of objects E15 and E17 can also be calculated separately.

[0152] After step S36, the reflectance is plotted on a graph (step S37). In a graph with wavelength as the X-axis and reflectance R as the Y-axis, the calculated reflectance R for each band is plotted. In this embodiment, the reflectance R for each band is plotted using the center value of the band (see reference). Figure 19 ).

[0153] Will Figure 19 The plotted reflectance and Figure 9 The 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 reflectance of object E11 (E12~E14) is plotted and... Figure 9The spectrophotometric reflectance curve of Fe is the closest. Therefore, image processing device 6 determines that object E11 is Fe. The plotting of the reflectance of objects E15 (E16, E18, E20) is... Figure 9 The reflectance curve of A1 in the image is the closest. Therefore, the image processing device 6 determines that object E15 is A1. The plotting of the reflectance R of objects E17 (E16, E19, E21) is... Figure 9 The spectrophotometric reflectance curve of Cu in the image is the closest. Therefore, the image processing device 6 determines that the object E17 is Cu.

[0154] As explained above, the inspection apparatus A according to this embodiment includes an illumination device 2 capable of illuminating a first light in a first band, a second light in a second band, and a reference light in a reference band that overlaps with the first and second bands; an imaging device 1 capable of imaging a sheet S (the object to be inspected) and outputting pixel signals; and an image processing device 6. The illumination device 2 illuminates the sheet S with the first light, the second light, and the reference light at different timings within one imaging time. The image processing device 6 calculates the reflectance in the first band (i.e., the first reflectance R31) and the reflectance in the second band (i.e., the second reflectance R32) of the object E based on the pixel signals, and determines the physical properties of the object E based on the first and second reflectances R31 and R32. That is, by illuminating the sheet S with the first light, the second light, and the reference light at different timings within one imaging time using the illumination device 2, an extracted image p of the object E based on the first light, an extracted image p of the object E based on the second light, and an extracted image p of the object E based on the reference light are generated in one image. Based on these three extracted images p, the first and second reflectivities R31 and R32 of the object E in the first and second bands can be calculated respectively, thus enabling the determination of the physical properties of the object E. Furthermore, since a single image contains extracted images p of the object E based on the first light, p of the object E based on the second light, and p of the object E based on the reference light, it is not necessary to photograph the sheet S separately for each band, thus reducing the increase in shooting time. Therefore, the physical properties of the object can be determined while suppressing the increase in shooting time.

[0155] Furthermore, the image processing device 6 determines the physical properties of the object E by comparing the first and second reflectivities R31 and R32 with spectrophotometric reflectance data representing the spectrophotometric reflectance of multiple substances. This allows for a more accurate determination of the physical properties of the object E.

[0156] Furthermore, when multiple objects E exist in the sheet S, the image processing device 6 generates the remaining image based on any two of the first image, the second image, and the reference image. The first image is an extracted image p of the object E based on the first light, the second image is an extracted image p of the object E based on the second light, and the reference image is an extracted image p of the object E based on the reference light. Therefore, even if any one of the first image, the second image, and the reference image overlaps with an extracted image p of another object E in the image P generated based on the pixel signal, the remaining image can be generated based on the other images among the first image, the second image, and the reference image, excluding the first image.

[0157] Furthermore, the image processing device 6 synthesizes the feature values ​​of the first image and the second image to generate a reference image. Thus, even if the reference image overlaps with other extracted images p in image p, a reference image can still be generated based on the first image and the second image.

[0158] Furthermore, the image processing device 6 generates the second image by subtracting the feature values ​​of the first image from the feature values ​​of the reference image. Thus, even if the first image overlaps with other extracted images p in the image p, the first image can be generated based on the reference image and the second image.

[0159] Furthermore, when multiple objects E exist in the sheet S, the image processing device 6 classifies the first image, the second image, and the reference image according to each of the multiple objects E. Additionally, the image processing device 6 calculates the first reflectance and the second reflectance based on the first image, the second image, and the reference image that are classified into the same group. Thus, when multiple objects E exist in the sheet S, the material properties can be determined according to each object E.

[0160] (Other implementation methods)

[0161] 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.

[0162] 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.

[0163] 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.

[0164] According to this disclosure, it is possible to determine the physical properties of an object while suppressing the increase in shooting time.

[0165] Industrial availability

[0166] 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: The lighting device is capable of illuminating a first light of a first band and a reference light of a reference band that overlaps with the first band; The imaging device captures images of the object being inspected and outputs pixel signals. as well as Image processing device The inspection method includes: The step of the illumination device illuminating the subject with the first light and the reference light at different time intervals within a shooting time; The image processing apparatus calculates the reflectance, i.e., the first reflectance, of the object in the first band based on a first image and a reference image based on the pixel signals, wherein the first image is an image of the object based on the first light, and the reference image is an image of the object based on the reference light; and The step of the image processing device determining the physical properties of the object based on the first reflectance.

2. An inspection method for detecting objects contained in an inspected body by taking pictures with an inspection device. The inspection device includes: The lighting device is capable of illuminating a first light of a first band, a second light of a second band, and a reference light of a reference band that overlaps with the first and second bands; The imaging device captures images of the object being inspected and outputs pixel signals. as well as Image processing device The inspection method includes: The step of the illumination device illuminating the subject with the first light, the second light and the reference light at different times within a shooting time; The step of the image processing device calculating the reflectance in the first band (i.e., the first reflectance) and the reflectance in the second band (i.e., the second reflectance) of the object based on the first image, the second image, and the reference image based on the pixel signals, wherein the first image is an image of the object based on the first light, the second image is an image of the object based on the second light, and the reference image is an image of the object based on the reference light; as well as The step of the image processing device determining the physical properties of the object based on the first reflectance and the second reflectance.

3. The inspection method according to claim 2, wherein, The image processing device determines the physical properties of the object by comparing the first reflectance and the second reflectance with spectrophotometric reflectance data representing the spectrophotometric reflectance of multiple substances.

4. The inspection method according to claim 2 or 3, wherein, include: In the case where there are multiple objects in the inspected body, the image processing device generates a remaining image based on any two of the first image, the second image, and the reference image.

5. The inspection method according to claim 4, wherein, include: The step of the image processing device synthesizing the feature values ​​of the first image and the second image to generate the reference image.

6. The inspection method according to claim 4, wherein, include: The step of the image processing device generating the second image by subtracting the feature values ​​of the first image from the feature values ​​of the reference image.

7. The inspection method according to claim 5 or 6, wherein, The characteristic quantity is the brightness value or lightness of the object.

8. The inspection method according to claim 2 or 3, wherein, Also includes: In the case where there are multiple objects in the subject being inspected, the image processing device generates the first image, the second image, and the reference image for each of the multiple objects. The step of the image processing device classifying the first image, the second image, and the reference image according to each of the plurality of objects; and The steps for calculating the first reflectance and the second reflectance based on the first image, the second image, and the reference image that are classified into the same group.

9. The inspection method according to any one of claims 1 to 3, wherein, include: The step of the image processing device using the reference image to determine the size of the object.

10. An inspection apparatus for detecting objects contained in an inspected body by taking an image, the inspection apparatus comprising: The lighting device is capable of illuminating a first light of a first band and a reference light of a reference band that overlaps with the first band; The imaging device captures images of the object being inspected and outputs pixel signals; and Image processing device The lighting device illuminates the subject with the first light and the reference light at different intervals within a single shooting time. The image processing device calculates the reflectance, i.e., the first reflectance, of the object in the first band based on the first image and the reference image based on the pixel signal, and determines the physical properties of the object based on the first reflectance. The first image is an image of the object based on the first light, and the reference image is an image of the object based on the reference light.

Images