JP5485761B2 - Defect detection apparatus and defect detection method - Google Patents

Description

  The present invention relates to a defect detection apparatus and a defect detection method for detecting an uneven defect generated on a surface to be inspected.

  Conventionally, various defect detection apparatuses for detecting uneven defects generated on the inspection target surface to be inspected have been developed. As an example of a conventional defect detection device, there are two areas: a bright area where reflected light of illumination light is detected by the camera if there is no defect on the inspection surface and a dark area where reflected light is not detected if there is no defect on the inspection surface. There is an apparatus that detects defects on a surface to be inspected using two regions (see, for example, Patent Documents 1 and 2). In this defect detection device, a light area and a dark area are formed on the surface to be inspected by providing a light shielding body between the camera and the surface to be inspected.

  As another example of a conventional defect detection apparatus, there is known an apparatus that detects an uneven defect by illuminating a surface to be inspected so that a boundary between a bright region and a dark region is formed on the surface to be inspected. (For example, refer to Patent Document 3). This defect detector irradiates a surface to be inspected using a special irradiation device so that a boundary between a bright region and a dark region is generated on the surface to be inspected, and an uneven defect exists at the boundary between the light region and the dark region. In this case, the unevenness defect on the surface to be inspected is detected by utilizing the fact that the bright / dark reversal portion is generated in the portion where the unevenness defect exists.

JP 2007-40853 A Japanese Patent Laid-Open No. 2005-257681 JP 2001-349716 A

  However, in the conventional defect detection device, it is necessary to add a light shielding body or use a special irradiation device in order to form a bright region and a dark region on the inspection target surface to be inspected. As a result, there is a problem that the device configuration becomes complicated.

  SUMMARY OF THE INVENTION The present invention has been made in view of the above points, and an object of the present invention is to provide a defect detection apparatus and a defect detection method capable of accurately detecting irregularities on a surface to be inspected with a low-cost and simple apparatus configuration. Is to provide.

A defect detection apparatus according to the present invention includes an irradiation device that irradiates light on an inspection target surface having diffuse reflectivity from an oblique direction, and an imaging device that images the inspection target surface irradiated with light from the irradiation device. And a processing device that detects defects related to the unevenness of the surface to be inspected using a captured image captured by the image capturing device, and directly irradiates a range in which the irradiation light of the irradiation device is directly irradiated on the surface to be inspected An area in which the diffused light generated by the diffusion of the irradiation light in the direct irradiation area is irradiated on the surface to be inspected is a diffused light irradiation area, and the imaging apparatus has the direct irradiation area and the diffused light irradiation. And the processing apparatus sets a first inspection area in the direct irradiation area in the captured image and a second in the diffused light irradiation area. Set the inspection area, said to the first inspection region and using the Luminance information of the second test area for detecting the defect, the region of low brightness than the surrounding in the direct radiation area and the diffuse light In the irradiation area, an extraction function for extracting each area having higher brightness than the surrounding area as a defect candidate area, and the defect exists in the defect candidate area when the size of the defect candidate area is larger than a preset threshold value. And a determination function for determining .

Defect detecting apparatus of the present invention, an illumination device for irradiating light from an oblique direction to the inspected surface having diffuse reflectivity of the test object, and an imaging device for imaging the inspected surface to which light is irradiated from the irradiation device And a processing device that detects defects related to the unevenness of the surface to be inspected using a captured image captured by the image capturing device, and directly irradiates a range in which the irradiation light of the irradiation device is directly irradiated on the surface to be inspected An area in which the diffused light generated by the diffusion of the irradiation light in the direct irradiation area is irradiated on the surface to be inspected is a diffused light irradiation area, and the imaging apparatus has the direct irradiation area and the diffused light irradiation. It is arranged and an area to contain the imaging area, wherein the processing unit, the second to the diffused light irradiation area and sets the first inspection region in the direct illumination area in the captured image Set the inspection area, it said for detecting the defect by using the luminance information of the first test area and the second inspection region, the regions of low intensity than the surrounding in the direct radiation area first region A first extraction function for extracting a region having higher brightness than the surroundings as a second region in the diffused light irradiation area, and a first size including the first region and having a preset size A first calculation function for calculating an average luminance of a setting area and an average luminance of a second setting area including the second area and having a preset size; and for each of the direct irradiation area and the diffused light irradiation area A binarization process using the binarization threshold value for each of the direct irradiation area and the diffused light irradiation area; Missing A second extraction function of extracting candidate regions, to have a determining function and the defect in the defect candidate region if the size is greater than a threshold set in advance of the defect candidate area exists Features .

  In this defect detection apparatus, the processing apparatus, as the second extraction function, performs binarization threshold when at least one of the first area and the second area is not extracted as the defect candidate area. It is preferable to re-extract the defect candidate area by changing the value and performing binarization processing again.

  The defect detection apparatus includes a type input device that inputs a type of the defect, and the processing device sets an inspection region used for detection of the defect according to the type input by the type input device. It is preferable to select from the inspection area and the second inspection area.

  The defect detection apparatus includes a transport device that transports the inspection target, and the imaging device has reached a direct irradiation area with a predetermined portion of the surface to be inspected as the inspection target is transported by the transport device. An image is taken at a timing and a timing at which the predetermined portion reaches the diffused light irradiation area, and the processing device captures an image when the predetermined portion reaches the direct irradiation area and the predetermined portion is at the diffused light irradiation area. It is preferable that the defect is detected using a captured image when reaching the position.

  In this defect detection apparatus, an unevenness amount input device for inputting the unevenness amount of the defect, and an optical axis between the irradiation device and the surface to be inspected according to the unevenness amount input by the unevenness amount input device It is preferable that the imaging device captures the surface to be inspected after the distance on the optical axis between the irradiation device and the surface to be inspected is varied.

  In this defect detection apparatus, it is preferable that the irradiation apparatus irradiates the surface to be inspected with diffused light.

  This defect detection apparatus preferably includes a light amount adjustment unit that reduces the amount of light incident on the imaging device.

The defect detection method of the present invention includes a first step of irradiating light on a surface to be inspected having diffuse reflectivity from an oblique direction, a second step of imaging the surface to be inspected, and the second step. A third step of detecting a defect related to the unevenness of the surface to be inspected using the captured image captured in the step, and a range in which the irradiation light is directly irradiated on the surface to be inspected is defined as a direct irradiation area, and On the inspection surface, a range irradiated with diffused light generated by diffusion of the irradiated light in the direct irradiation area is defined as a diffused light irradiation area. In the second step, the direct irradiation area, the diffused light irradiation area, In the third step, the first inspection area is set in the direct irradiation area in the captured image and the diffused light irradiation area is set in the third step. Set 2 of the inspection area, around in the first inspection area and with Luminance information of the second inspection region, the direct lower luminance than the surrounding in the irradiation area region and the diffused light irradiation area Each region having higher luminance is extracted as a defect candidate region, and when the size of the defect candidate region is larger than a preset threshold, it is determined that the defect exists in the defect candidate region, and the defect is detected. It is characterized by doing.
The defect detection method of the present invention includes a first step of irradiating light on a surface to be inspected having diffuse reflectivity from an oblique direction, a second step of imaging the surface to be inspected, and the second step. A third step of detecting a defect related to the unevenness of the surface to be inspected using the captured image captured in the step, and a range in which the irradiation light is directly irradiated on the surface to be inspected is defined as a direct irradiation area, and On the inspection surface, a range irradiated with diffused light generated by diffusion of the irradiated light in the direct irradiation area is defined as a diffused light irradiation area. In the second step, the direct irradiation area, the diffused light irradiation area, In the third step, the first inspection area is set in the direct irradiation area in the captured image and the diffused light irradiation area is set in the third step. 2 inspection areas are set, and using the luminance information of the first inspection area and the second inspection area, an area having lower luminance than the surrounding area is extracted as the first area in the direct irradiation area, In the diffused light irradiation area, an area having higher brightness than the surrounding is extracted as a second area, and the average brightness of the first setting area including the first area and having a preset size and the second area are extracted. And calculating the average luminance of the second setting area having a preset size, for each of the direct irradiation area and the diffused light irradiation area, to determine a binarization threshold using the average luminance, For each direct irradiation area and diffused light irradiation area, a binarization process is performed using the binarization threshold value to extract a defect candidate region, and a threshold value in which the size of the defect candidate region is set in advance Greater It determines that the defect exists in the defect candidate region if already there and detects the defect.

  According to the present invention, the direct irradiation area where the irradiation light of the irradiation apparatus is directly irradiated on the inspection target surface to be inspected, and the diffused light generated by the diffusion of the irradiation light in the direct irradiation area is irradiated on the inspection target surface. Since unevenness defects can be detected using the luminance information of at least one of the diffused light irradiation area, for example, a low-cost and simple device configuration can be used without a light shield or special irradiation device. It is possible to accurately detect uneven defects on the surface to be inspected.

It is the schematic which shows the structure of the defect detection apparatus which concerns on Embodiment 1. FIG. It is a figure for demonstrating a direct irradiation area and a diffused light irradiation area in the picked-up image imaged with the imaging device which concerns on the same as the above. In the picked-up image picked up by the image pickup apparatus according to the above, (a) shows a case where a defect exists in the diffused light irradiation area, and (b) shows a case where a defect exists in the direct irradiation area. It is a figure which shows a defect area | region in the defect detection apparatus which concerns on the same as the above. It is a flowchart which shows the defect detection method which concerns on the same as the above. 6 is a flowchart illustrating a defect detection method according to the second embodiment. In the defect detection apparatus according to the third embodiment, (a) is a diagram illustrating a captured image when the average luminance is 25 and the binarization threshold is 60, and (b) illustrates a main part of the binarized image. FIG. 4C is a diagram showing a captured image when the average luminance is 60 and the binarization threshold is 40, and FIG. 4D is a diagram showing a main part of the binarized image. It is a flowchart which shows the defect detection method which concerns on the same as the above. 6 is a flowchart illustrating a defect detection method according to a fourth embodiment. It is the schematic which shows the structure of the defect detection apparatus which concerns on Embodiment 5. FIG. It is a flowchart which shows the defect detection method which concerns on the same as the above. In the captured image imaged with the imaging device which concerns on Embodiment 6, (a) is a figure which shows the case where a defect exists in a direct irradiation area, (b) is a figure which shows the case where a defect exists in a diffused light irradiation area. is there. In the defect detection apparatus according to the above, (a) shows a drive signal, and (b) shows an imaging signal. It is a flowchart which shows the defect detection method which concerns on the same as the above. It is the schematic which shows the structure of the defect detection apparatus which concerns on Embodiment 7. FIG. It is a flowchart which shows the defect detection method which concerns on the same as the above. It is the schematic which shows the structure of the defect detection apparatus which concerns on Embodiment 8. FIG. It is the schematic which shows the structure of the defect detection apparatus which concerns on Embodiment 9. FIG. It is a figure which shows the polarizing filter which concerns on the same as the above.

(Embodiment 1)
As shown in FIG. 1, the defect detection apparatus according to the first embodiment is an apparatus that detects a concavo-convex defect generated on a surface B to be inspected A. The defect detection device according to the present embodiment includes an irradiation device 1, an imaging device 2, a processing device 3, and a transport device 4.

  The inspection target A is, for example, wood from which the surface B to be inspected is polished. Examples of the timber include wooden flooring. The surface B to be inspected has diffuse reflectivity. Note that the surface B to be inspected may be colored and painted.

  The irradiation device 1 is a line illuminating device that emits line-shaped light using, for example, an LED or a fluorescent lamp, and irradiates light on the surface B to be inspected A from an oblique direction (attachment angle θ1). That is, the irradiation surface 1 is irradiated with the irradiation light from the irradiation device 1. The attachment angle θ1 of the irradiation device 1 is 15 degrees. The illumination from the irradiation device 1 may be multicolor illumination.

  The imaging device 2 is, for example, an area sensor camera or a line sensor camera, and light that has passed through the surface to be inspected B from the irradiation device 1 is incident thereon. The mounting angle θ2 of the imaging device 2 is obliquely upward with respect to the inspection object A, for example. In the present embodiment, the attachment angle θ2 is 30 degrees. The imaging device 2 captures an image of the inspection object A that is in either the state of conveyance stop or the state of conveyance.

  The processing device 3 detects a concavo-convex defect on the surface B to be inspected using the captured image captured by the imaging device 2. That is, the processing device 3 performs defect detection processing using an image obtained by imaging the inspection target A that is in either the transport state or the transport stop state.

  The conveyance device 4 is, for example, a drive conveyor and conveys the inspection target A. In addition, if the conveying apparatus 4 is a means which can convey the test object A, it will not be limited to the above.

  As shown in FIG. 2, a range in which the irradiation light of the irradiation apparatus 1 is directly irradiated on the inspection surface B is defined as a direct irradiation area C. A range irradiated with diffused light generated by diffusion of irradiation light in the direct irradiation area C on the inspection surface B is defined as a diffusion light irradiation area D.

  In the diffused light irradiation area D, since the light is irradiated from all directions and angles with respect to the defect, the defect is easily shaded. That is, a bright and dark part is likely to occur in the defect. The same effect can be obtained by directly irradiating the defect with light. However, since the light is direct light, it may be difficult to detect the bright and dark part due to the wraparound of the light.

  In the present embodiment, a light and dark region is more likely to be generated in the diffused light irradiation area D by irradiating the defect with the diffused light from the direct irradiation area C.

  As shown in FIG. 2, the imaging device 2 is arranged so as to include a direct irradiation area C and a diffused light irradiation area D in the imaging region. Two areas C and D with the camera visual axis O as the center enter the captured image. As an example, the diffused light irradiation area D is an area whose center is usually 20 mm to 25 mm away from the center of the direct irradiation area C (distance L in FIG. 2). The diffused light irradiation area D is set by the range irradiated with the diffused light and the resolution matched to the amount of defect unevenness to be evaluated.

  The processing device 3 includes, for example, a microprocessor (MPU) as a main component, and sets a first inspection region in the direct irradiation area C and a second inspection region in the diffused light irradiation area D in the captured image. The processing device 3 detects a defect using luminance information of at least one of the first inspection region and the second inspection region. 3A shows a case where a defect E exists in the diffused light irradiation area D, and FIG. 3B shows a case where a defect E exists in the direct irradiation area C. FIG. FIG. 4 shows a defect area of the binarized image.

  Next, a defect detection method using the defect detection apparatus according to the present embodiment will be described with reference to FIG. First, the irradiation device 1 irradiates the inspection surface B of the inspection object A, and the imaging device 2 images the inspection surface B (S1 in FIG. 5). Thereafter, the processing device 3 extracts (cuts out) the irradiation area C directly from the captured image (S2). Thereafter, the processing device 3 performs binarization processing on the direct irradiation area C using the binarization threshold (S3). The processing device 3 detects (extracts) a black region having a low pixel value from the binarized image and sets it as a detection region (S4). Thereafter, it is determined whether or not the detection area is larger than the set area (S5). If the detection area is larger than the set area, it is determined that there is a defect in the detection area and the inspection object A is defective (S6). When the detection area is equal to or smaller than the set area, the processing device 3 determines that there is no defect in the detection area, and determines that the inspection target A is a non-defective product (S7). The processing device 3 executes the processing from step S5 to step S7 for all the detection areas (S8). Thereafter, since the diffused light irradiation area D is not extracted (S9), the diffused light irradiation area D is extracted (cut out) (S10). Thereafter, the processing device 3 performs binarization processing on the diffused light irradiation area D using the binarization threshold (S3). The processing device 3 detects (extracts) a white region having a high pixel value from the binarized image and sets it as a detection region (S4). Thereafter, the processing device 3 executes the processing from step S5 to step S8. Thereafter, the processing in both the direct irradiation area C and the diffused light irradiation area D is completed (S9), and the defect detection operation ends.

  As described above, according to the defect detection apparatus and the defect detection method of the present embodiment, the direct irradiation area C where the irradiation light of the irradiation apparatus 1 is directly irradiated on the inspection surface B of the inspection object A and the direct irradiation on the inspection surface B. Since the unevenness defect can be detected by using the luminance information with the diffused light irradiation area D irradiated with the diffused light generated by the diffusion of the irradiated light in the area C, for example, a light shield or a special irradiation device is provided. Even if it is not, it is possible to accurately detect the concavo-convex defect of the inspection surface B of the inspection object A with a low-cost and simple apparatus configuration.

(Embodiment 2)
The defect detection apparatus according to the second embodiment is different from the defect detection apparatus according to the first embodiment in that a defect is detected not from a binarized image but from a captured image itself. Hereinafter, the defect detection apparatus of this embodiment will be described with reference to FIGS. Note that the description of the same components as those in the first embodiment is omitted.

  The processing device 3 (see FIG. 1) of the present embodiment has an extraction function and a determination function. As the extraction function, the processing device 3 uses, as the extraction function, a defect candidate region for a region having lower brightness than the surroundings in the direct irradiation area C (see FIG. 2) and a region having higher brightness than the surroundings in the diffused light irradiation area D (see FIG. 2). Extract as

  As a determination function, the processing device 3 determines that a defect exists in the defect candidate area when the size of the defect candidate area is larger than a preset threshold value.

  Even in the same defect, the direct irradiation area C and the diffused light irradiation area D are different in appearance. Therefore, a defect is detected using this appearance. In the case of a convex defect, a bulge occurs as a shadow in the direct irradiation area C. In the case of a concave defect, a dent is generated as a bright spot in the diffused light irradiation area D.

  Next, a defect detection method using the defect detection apparatus according to the present embodiment will be described with reference to FIG. First, the irradiation apparatus 1 irradiates the inspection surface B of the inspection object A, and the imaging apparatus 2 images the inspection surface B (S11 in FIG. 6). Thereafter, the processing device 3 extracts (cuts out) the irradiation area C directly from the captured image (S12). Thereafter, the processing device 3 extracts a region having a luminance equal to or lower than “minimum luminance + α” from the direct irradiation area C of the captured image, and sets it as a detection region (S13). Further, the processing device 3 extracts (cuts out) the diffused light irradiation area D from the captured image (S14). Thereafter, the processing device 3 extracts a region having a luminance of “maximum luminance−β” or more from the diffused light irradiation area D of the captured image, and sets it as a detection region (S15). Thereafter, it is determined whether or not the detection area area is larger than the set area area for each of the detection areas extracted in step S13 and step S15 (S16). If the detection area is larger than the set area, it is determined that there is a defect in the detection area and the inspection object A is defective (S17). When the detection area is equal to or smaller than the set area, the processing device 3 determines that there is no defect in the detection area, and determines that the inspection target A is a non-defective product (S18). The processing device 3 executes the processing from step S16 to step S18 for all the detection areas (S19), and ends the defect detection operation.

  As described above, according to the defect detection apparatus and the defect detection method of the present embodiment, even in the case of an uneven defect that is difficult to detect with a small amount of unevenness, a luminance difference occurs between the uneven defect and the surroundings in the captured image. Irregularity defects can be easily detected.

(Embodiment 3)
The defect detection apparatus according to the third embodiment is different from the defect detection apparatus according to the first embodiment in that the binarization threshold value is changed according to the average luminance. Hereinafter, the defect detection apparatus of this embodiment will be described with reference to FIGS. Note that the description of the same components as those in the first embodiment is omitted.

  The surface B to be inspected of the inspection target A has a different appearance on the captured image because the surface state and the paint color are different depending on the type. That is, the average brightness of the imaging range is different. Since there is a luminance difference of 35 depending on the product type, if the binarization process is performed with the same binarization threshold value, accurate extraction cannot be performed, so the binarization threshold value is varied.

  The processing device 3 (see FIG. 1) of the present embodiment has a first extraction function, a first calculation function, a second calculation function, a second extraction function, and a determination function. .

  As a first extraction function, the processing device 3 extracts a region having a lower brightness than the surroundings in the direct irradiation area C as a first region, and a region having a higher brightness than the surroundings in the diffused light irradiation area D as the second region. Extract as a region.

  The processing device 3 has, as a first calculation function, an average luminance of a first setting area including a first area and a predetermined size and a first size including a second area and a predetermined size. The average brightness of the two setting areas is calculated. The processing device 3 extracts a predetermined area from the imaging range and calculates the average luminance. The area for calculating the average luminance is arbitrarily set. However, in order to reflect the surface state more, each imaging range is set as wide as possible. An example is 100 × 30 pixels.

  As the second calculation function, the processing device 3 obtains a binarization threshold value for each of the direct irradiation area C and the diffused light irradiation area D using the average luminance calculated by the first calculation function. That is, a binarization threshold value corresponding to the average luminance is arbitrarily set.

  The processing apparatus 3 performs a binarization process using a binarization threshold as a second extraction function, and extracts a defect candidate area.

  As a determination function, the processing device 3 determines that a defect exists in the defect candidate area when the size of the defect candidate area is larger than a preset threshold value. That is, the processing device 3 detects the defect by comparing the area values of the extraction regions.

  Next, a defect detection method using the defect detection apparatus according to the present embodiment will be described with reference to FIG. First, the irradiation apparatus 1 irradiates the inspection surface B of the inspection object A, and the imaging apparatus 2 images the inspection surface B (S21 in FIG. 8). Thereafter, the processing device 3 extracts (cuts out) the irradiation area C directly from the captured image (S22). Thereafter, the processing device 3 extracts the lowest luminance region (region having a luminance equal to or lower than “lowest luminance + α”) from the direct irradiation area C of the captured image (S23). Thereafter, the processing device 3 calculates an average luminance of 100 × 30 pixels around the extraction region (extraction pixel) (S24). Since it is the direct irradiation area C (S25), it is determined whether or not the average luminance is greater than 220 (S26). If the average luminance is greater than 220, the binarization threshold is set to 160 (S27). If the average luminance is 220 or less, the binarization threshold is set to 120 (S28). Thereafter, the processing apparatus 3 performs binarization processing on the direct irradiation area C using the set binarization threshold (S32). The processing device 3 extracts a black area having a small pixel value from the binarized image and sets it as a detection area (S33). Thereafter, it is determined whether or not the detection area is larger than the set area (S34). If the detection area is larger than the set area, it is determined that there is a defect in the detection area and the inspection target A is defective (S35). When the detection area is equal to or smaller than the set area, the processing device 3 determines that there is no defect in the detection area, and determines that the inspection target A is a good product (S36). The processing device 3 executes the processing from step S34 to step S36 for all the detection areas (S37). Thereafter, since the diffused light irradiation area D is not extracted (S38), the diffused light irradiation area D is extracted (cut out) (S39). Thereafter, the processing device 3 extracts the highest luminance region (region having a luminance of “highest luminance−β” or higher) from the diffused light irradiation area D of the captured image (S23). Thereafter, the processing device 3 calculates an average luminance of 100 × 30 pixels around the extraction region (extraction pixel) (S24). Thereafter, it is determined whether or not the average luminance is greater than 30 (S29). If the average luminance is greater than 30, the binarization threshold is set to 40 (S30). If the average luminance is 30 or less, the binarization threshold is set to 60 (S31). Thereafter, the processing device 3 performs binarization processing on the diffused light irradiation area D using the set binarization threshold (S32). The processing device 3 extracts a white region having a large pixel value from the binarized image (S33). Thereafter, the processing from step S34 to step S37 is executed. Thereafter, the processing in both the direct irradiation area C and the diffused light irradiation area D is completed (S38), and the defect detection operation is terminated.

  As described above, according to the defect detection device and the defect detection method of the present embodiment, the influence of the state of the surface B to be inspected can be reduced, so that a minute uneven defect can be detected.

(Embodiment 4)
The defect detection apparatus according to the fourth embodiment is different from the defect detection apparatus according to the third embodiment in that the binarization threshold can be reset. Hereinafter, the defect detection apparatus of this embodiment will be described with reference to FIG. Note that description of the same components as those in the third embodiment is omitted.

  When at least one of the first region and the second region is not extracted as a defect candidate region, the processing device 3 according to the present embodiment changes the binarization threshold value to 2 again as the second extraction function. The defect candidate area is re-extracted by performing the value processing. When the highest luminance region or the lowest luminance region for which the average luminance is calculated is not detected in the detection region, the processing device 3 resets the binarization threshold value, performs the binarization process, and detects the detected again A determination is made in the region.

  By performing the binarization process twice for each area C and D by the above procedure, the highest luminance region and the lowest luminance region are detected in the imaging range. A defect can be accurately detected by setting a plurality of binarization threshold values and performing binarization processing a plurality of times.

  Next, a defect detection method using the defect detection apparatus according to the present embodiment will be described with reference to FIG. First, the irradiation apparatus 1 irradiates the inspection surface B of the inspection object A, and the imaging apparatus 2 images the inspection surface B (S41 in FIG. 9). Thereafter, the processing device 3 extracts (cuts out) the irradiation area C directly from the captured image (S42). Thereafter, the processing device 3 extracts the lowest luminance region (region having a luminance equal to or lower than “lowest luminance + α”) from the direct irradiation area C of the captured image (S43). Thereafter, the processing device 3 calculates an average luminance of 100 × 30 pixels around the extraction region (extraction pixel) (S44). When it is the direct irradiation area C (S45), it is determined whether or not the average luminance is greater than 220 (S46). If the average luminance is greater than 220, the binarization threshold is set to 140 (S47). If the average luminance is 220 or less, the binarization threshold is set to 120 (S48). Thereafter, the processing device 3 performs binarization processing on the direct irradiation area C using the set binarization threshold (S52). The processing device 3 extracts a black area having a small pixel value from the binarized image and sets it as a detection area (S53). Thereafter, it is determined whether or not the detection area is larger than the set area (S54). If the detection area is larger than the set area, it is determined that there is a defect in the detection area and the inspection object A is defective (S55). When the detection area is equal to or smaller than the set area, the processing device 3 determines that there is no defect in the detection area, and determines that the inspection target A is a non-defective product (S56). The processing device 3 executes the processing from step S54 to step S56 for all the detection areas (S57).

  Thereafter, it is determined whether or not secondary extraction described later has been completed (S58). If the secondary extraction has not been completed, it is determined whether or not the lowest luminance region has been extracted (S59). If the minimum luminance area is not extracted, the process is being performed on the direct irradiation area C (S60), and the binarization threshold is reset to 160 (S61). Thereafter, the secondary extraction ends (S63), and binarization processing is performed using the reset binarization threshold (S52).

  Thereafter, since the diffused light irradiation area D is not extracted (S64), the diffused light irradiation area D is extracted (cut out) (S65). Then, the process of step S43 and step S44 is performed with respect to the diffused light irradiation area D. Thereafter, it is determined whether or not the average luminance is greater than 30 (S49). If the average luminance is greater than 30, the binarization threshold is set to 70 (S50). If the average luminance is 30 or less, the binarization threshold is set to 80 (S51). Thereafter, the processing device 3 performs binarization processing on the diffused light irradiation area D using the set binarization threshold (S52). The processing device 3 extracts a white area having a large pixel value from the binarized image and sets it as a detection area (S53). Thereafter, the processing from step S54 to step S57 is executed.

  Thereafter, it is determined whether or not the secondary extraction is completed (S58). If the secondary extraction has not been completed, it is determined whether or not the highest luminance region has been extracted (S59). If the highest brightness area is not extracted, the process is being performed on the diffused light irradiation area D (S60), and the binarization threshold is reset to 60 (S62). Thereafter, the secondary extraction ends (S63), and binarization processing is performed using the reset binarization threshold (S52). Thereafter, the processing in both the direct irradiation area C and the diffused light irradiation area D is completed (S64), and the defect detection operation ends.

  As described above, according to the defect detection apparatus and the defect detection method of the present embodiment, an optimal binarization threshold value can be set according to the luminance information of the captured image, so that a minute uneven defect can be detected. .

(Embodiment 5)
The defect detection apparatus according to the fifth embodiment is different from the defect detection apparatus according to the first embodiment (see FIG. 1) in that an input device 5 is provided as shown in FIG. Hereinafter, the defect detection apparatus of this embodiment will be described with reference to FIGS. In addition, about the component similar to Embodiment 1, the same code | symbol is attached | subjected and description is abbreviate | omitted.

  The input device 5 is, for example, a touch panel or a keyboard, and a defect type is input. The input device 5 is connected to the processing device 3 and transmits an input value (input information) to the processing device 3. The input device 5 corresponds to the type input device of the present invention.

  The processing device 3 of the present embodiment performs a corresponding process based on the input value from the input device 5. The processing device 3 selects an inspection region to be used for defect detection from the first inspection region and the second inspection region according to the type input by the input device 5.

  Next, a defect detection method using the defect detection apparatus according to the present embodiment will be described with reference to FIG. First, the irradiation apparatus 1 irradiates the inspection surface B of the inspection object A, and the imaging apparatus 2 images the inspection surface B (S71 in FIG. 11). Thereafter, the processing device 3 determines whether to extract only the convex defect or both the concave defect and the convex defect (S72). When extracting only the convex defect, the processing device 3 extracts (cuts out) the irradiation area C directly from the captured image (S73). Thereafter, the processing device 3 extracts the lowest luminance region (region having a luminance equal to or lower than “lowest luminance + α”) from the direct irradiation area C of the captured image (S75). Thereafter, the processing device 3 calculates an average luminance of 100 × 30 pixels around the extraction region (extraction pixel) (S76). When it is the direct irradiation area C (S77), it is determined whether or not the average luminance is larger than 220 (S78). If the average luminance is greater than 220, the binarization threshold is set to 140 (S79). When the average luminance is 220 or less, the binarization threshold is set to 120 (S80). Thereafter, the processing device 3 performs a binarization process on the direct irradiation area C using the set binarization threshold (S84). The processing device 3 extracts a black region having a small pixel value from the binarized image and sets it as a detection region (S85). Thereafter, it is determined whether or not the detection area is larger than the set area (S86). If the detection area is larger than the set area, it is determined that there is a defect in the detection area and the inspection target A is defective (S87). When the detection area is equal to or smaller than the set area, the processing device 3 determines that there is no defect in the detection area, and determines that the inspection target A is a good product (S88). The processing device 3 executes the processing from step S86 to step S88 for all the detection areas (S89).

  Thereafter, it is determined whether or not secondary extraction described later is completed (S90). If the secondary extraction has not been completed, it is determined whether or not the lowest luminance region has been extracted (S91). If the lowest luminance area is not extracted, the process is being performed on the direct irradiation area C (S92), and the binarization threshold is reset to 160 (S93). Thereafter, the secondary extraction is completed (S95), and binarization processing is performed using the reset binarization threshold (S84). Thereafter, since the secondary extraction has already been completed (S90), the defect detection operation is terminated.

  On the other hand, when detecting both a concave defect and a convex defect in step S72, the processing apparatus 3 extracts the diffused light irradiation area D (S74). Thereafter, the processing device 3 extracts the highest luminance region (region having a luminance of “highest luminance−β” or higher) from the diffused light irradiation area D of the captured image (S75). Thereafter, the processing device 3 calculates an average luminance of 100 × 30 pixels around the extraction region (extraction pixel) (S76). When it is the diffused light irradiation area D (S77), it is determined whether or not the average luminance is greater than 30 (S81). If the average luminance is greater than 30, the binarization threshold is set to 70 (S82). If the average luminance is 30 or less, the binarization threshold is set to 80 (S83). Thereafter, the processing apparatus 3 performs binarization processing on the diffused light irradiation area D using the set binarization threshold (S84). The processing device 3 extracts a white area having a large pixel value from the binarized image and sets it as a detection area (S85). Thereafter, it is determined whether or not the detection area is larger than the set area (S86). If the detection area is larger than the set area, it is determined that there is a defect in the detection area and the inspection target A is defective (S87). When the detection area is equal to or smaller than the set area, the processing device 3 determines that there is no defect in the detection area, and determines that the inspection target A is a good product (S88). The processing device 3 executes the processing from step S86 to step S88 for all the detection areas (S89).

  Thereafter, it is determined whether or not secondary extraction described later is completed (S90). If the secondary extraction has not been completed, it is determined whether or not the highest luminance region has been extracted (S91). If the highest luminance area is not extracted, the process is being performed on the diffused light irradiation area D (S92), and the binarization threshold is reset to 60 (S94). Thereafter, the secondary extraction is completed (S95), and binarization processing is performed using the reset binarization threshold (S84). Thereafter, since the secondary extraction has already been completed (S90), the defect detection operation is terminated.

  As described above, according to the defect detection apparatus of the present embodiment, the processing time can be shortened and the selected type of defect can be accurately detected even when the number of the concavo-convex defects on the inspection surface B increases. .

(Embodiment 6)
The defect detection apparatus according to the sixth embodiment is different from the defect detection apparatus according to the fourth embodiment in that one defect is detected in both the direct irradiation area C and the diffused light irradiation area D. Hereinafter, the defect detection apparatus of this embodiment will be described with reference to FIGS. In addition, description is abbreviate | omitted about the component similar to Embodiment 4. FIG.

  In the imaging apparatus 2 of the present embodiment, when the inspection target A is transported by the transport device 4, the predetermined part of the surface B to be inspected directly reaches the irradiation area C and the predetermined part reaches the diffused light irradiation area D. Images are taken at the timing. While the driving signal shown in FIG. 13A is H, the inspection object A is conveyed by the conveying device 4. The imaging device 2 of the present embodiment captures two captured images by generating the imaging timing signal twice as shown in FIG. 13B while the transport device 4 is driven.

  The processing apparatus 3 according to the present embodiment uses a captured image obtained when the predetermined portion directly reaches the irradiation area C and a captured image obtained when the predetermined portion reaches the diffused light irradiation area D. Is detected. As shown in FIG. 12, the processing device 3 according to the present embodiment determines a defect if the deviation amount δ is within a predetermined number of pixels. As an example, if the deviation amount δ is within ± 10 pixels, it is determined as a defect.

  The processing device 3 detects a defect only when the area value of the detection area in the direct irradiation area C is larger than the set area value (defect is determined) and is close to the X coordinate of the detection area in the diffused light irradiation area D. judge.

  Next, a defect detection method using the inspection detection apparatus according to the present embodiment will be described with reference to FIG. First, the irradiation apparatus 1 irradiates the inspection surface B of the inspection object A, and the imaging apparatus 2 images the inspection surface B (S101 in FIG. 14). Thereafter, the processing device 3 extracts (cuts out) the irradiation area C directly from the captured image (S102). Thereafter, the processing device 3 extracts the lowest luminance region (region having a luminance equal to or lower than “lowest luminance + α”) from the direct irradiation area C of the captured image (S103). Thereafter, the processing device 3 calculates an average luminance of 100 × 30 pixels around the extraction region (extraction pixel) (S104). When it is the direct irradiation area C (S105), it is determined whether or not the average luminance is larger than 220 (S106). If the average luminance is greater than 220, the binarization threshold is set to 140 (S107). If the average luminance is 220 or less, the binarization threshold is set to 120 (S108). Thereafter, the processing device 3 performs a binarization process on the direct irradiation area C using the set binarization threshold (S112). The processing device 3 extracts a black region having a small pixel value from the binarized image and sets it as a detection region (S113). Thereafter, since the diffused light irradiation area D is not extracted (S114), the processing device 3 extracts (cuts out) the diffused light irradiation area D from the captured image (S115). Thereafter, the processing device 3 extracts a maximum luminance region (region having a luminance equal to or higher than “maximum luminance−β”) from the diffused light irradiation area D of the captured image (S103). Thereafter, the processing device 3 calculates an average luminance of 100 × 30 pixels around the extraction region (extraction pixel) (S104). When it is the diffused light irradiation area D (S105), it is determined whether or not the average luminance is greater than 30 (S109). If the average luminance is greater than 30, the binarization threshold is set to 70 (S110). If the average luminance is 30 or less, the binarization threshold is set to 80 (S111). Thereafter, the processing apparatus 3 performs binarization processing on the diffused light irradiation area D using the set binarization threshold (S112). The processing device 3 extracts a white area having a large pixel value from the binarized image and sets it as a detection area (S113).

  Then, the detection area of the direct irradiation area C is read in order (S116). It is determined whether or not the read detection area is larger than the set area (S117). When the detection area area is larger than the set area area, the detection area of the diffused light irradiation area D is read (S118). It is determined whether or not the X coordinate of the read detection area is within ± 10 pixels of the X coordinate of the detection area read in the direct irradiation area C (S119). When the X coordinate of the read detection area is within ± 10 pixels of the X coordinate of the detection area read in the direct irradiation area C, it is determined that a defect exists in the detection area and the inspection target A is defective (S120). . On the other hand, when the X coordinates of all the detection areas read out in the diffused light irradiation area D are ± 10 pixels or more of the X coordinates of the detection areas read out in the direct irradiation area C (S119, S121), the processing device 3 Then, it is determined that there is no defect in the detection area, and it is determined that the inspection target A is a non-defective product (S122). The processing device 3 executes the processing from step S116 to step S122 for all detection areas in the direct irradiation area C (S123).

  Thereafter, it is determined whether or not secondary extraction described later is completed (S124). If the secondary extraction has not been completed, it is determined whether or not the lowest luminance region and the highest luminance region are extracted (S125). When the lowest luminance region and the highest luminance region are not extracted, the binarization threshold value of the direct irradiation area C is reset to 160, and the binarization threshold value of the diffused light irradiation area D is reset to 60 (S126). ). Thereafter, the secondary extraction ends (S127), and binarization processing is performed using the reset binarization threshold (S112). Thereafter, the secondary extraction ends (S124), and the defect detection operation ends.

  As described above, according to the defect detection apparatus and the defect detection method of the present embodiment, defect detection using the direct irradiation area C and defect detection using the diffused light irradiation area D are used in combination on a predetermined portion of the inspection surface B. Therefore, it is possible to perform a more strict defect determination process, and it is possible to detect uneven defects with high accuracy. That is, since the determination is performed using the imaging information of the two areas C and D, a double check is performed, and erroneous detection can be reduced.

(Embodiment 7)
The defect detection apparatus according to the seventh embodiment is different from the defect detection apparatus according to the fifth embodiment in that an input device 5 and a drive device 6 are provided as shown in FIG. Hereinafter, the defect detection apparatus of this embodiment will be described with reference to FIGS. In addition, about the component similar to Embodiment 5, the same code | symbol is attached | subjected and description is abbreviate | omitted.

  The input device 5 of the present embodiment is a touch panel, a keyboard, or the like, and a defect unevenness amount is input. The input device 5 of the present embodiment corresponds to the unevenness amount input device of the present invention.

  The processing device 3 of the present embodiment sets a driving amount for driving the irradiation device 1 based on the input value from the input device 5.

  The driving device 6 varies the distance on the optical axis between the irradiation device 1 and the surface B to be inspected according to the amount of unevenness input by the input device 5. As the driving device 6, the irradiation device 1 has a drive mechanism such as a linear motion cylinder, and drives the irradiation device 1 in the same direction as the irradiation direction. The driving amount of the driving device 6 is calculated by the processing device 3 based on the unevenness amount input from the input device 5 and the imaging information.

  In the present embodiment, the average luminance that should be in the diffused light irradiation area D is set according to the amount of unevenness input to the input device 5, and then the average luminance of a predetermined range set in the diffused light irradiation area D is calculated. Then, a drive amount corresponding to the actual average brightness is calculated with respect to the desired average brightness of the set diffused light irradiation area D, and the drive mechanism is driven.

  The imaging device 2 of the present embodiment captures an image after the distance on the optical axis between the irradiation device 1 and the surface B to be inspected is varied.

  The area of the bright area and the dark area in the light and dark area of the uneven defect differs depending on the amount of unevenness to be detected. If the unevenness amount is large, the bright area is detected in a large area, and therefore, it is relatively less affected by the surrounding luminance. However, if the unevenness amount is small, the detection area of the bright area is small and easily affected. Therefore, the average luminance to be compared is set so that the peripheral luminance may be high if the detected unevenness amount is large and low if it is small.

  If the drive amount is larger than the average brightness to be compared, the drive amount is driven away from the inspection object A so as to be dark, and if the drive amount is small, the drive amount is increased. By performing the driving operation in this way, it is possible to configure an optimal illumination condition according to the unevenness amount of the uneven defect and to optimize the imaging information (captured image), so that the defect can be detected more accurately.

  Next, a defect detection method using the defect detection apparatus according to the present embodiment will be described with reference to FIG. First, the detected unevenness amount is read (S131 in FIG. 16). It is determined whether the unevenness is less than 50 μm (S132). When the unevenness amount is 50 μm or more, the comparative average luminance is set to 60 (S133). When the unevenness is less than 50 μm, the comparative average luminance is set to 40 (S134). Thereafter, the irradiation apparatus 1 irradiates the inspection surface B of the inspection object A, and the imaging apparatus 2 performs preliminary imaging (S135). Thereafter, the diffused light irradiation area D is extracted (cut out) (S136). Thereafter, the average luminance within the predetermined range is calculated (S137). Thereafter, it is determined whether or not the calculated average luminance is less than the comparative average luminance (S138). When the average luminance is equal to or higher than the comparative average luminance, the driving amount is set to +40 mm (S139). When the average luminance is less than the comparative average luminance, the driving amount is set to −40 mm (S140). Thereafter, the irradiation apparatus 1 is driven (S141).

  Thereafter, the imaging device 2 images the inspection surface B of the inspection object A (S142). Thereafter, the processing device 3 extracts (cuts out) the irradiation area C directly from the captured image (S143). Thereafter, the processing device 3 performs binarization processing on the direct irradiation area C using the binarization threshold (S144). The processing device 3 extracts a black area having a small pixel value from the binarized image and sets it as a detection area (S145). Thereafter, it is determined whether the detection area is larger than the set area (S146). When the detection area is equal to or smaller than the set area, the processing device 3 determines that there is no defect in the detection area, and determines that the inspection target A is a non-defective product (S147). If the detection area is larger than the set area, it is determined that there is a defect in the detection area and the inspection target A is defective (S148). The processing device 3 executes the processing from step S146 to step S148 for all the detection areas (S149). Thereafter, since the extraction of the diffused light irradiation area D is not completed (S150), the diffused light irradiation area D is extracted (cut out) (S151). Thereafter, the processing device 3 performs binarization processing on the diffused light irradiation area D using the binarization threshold (S144). The processing device 3 extracts a white region having a large pixel value from the binarized image and sets it as a detection region (S145). Thereafter, the processing from step S146 to step S149 is executed. Thereafter, the processing in both the direct irradiation area C and the diffused light irradiation area D is completed (S150), the irradiation apparatus 1 is returned to the initial drive position (S152), and the defect detection operation is terminated.

  As described above, according to the defect detection device and the defect detection method of the present embodiment, an optimal captured image corresponding to the amount of unevenness to be detected can be acquired, and thus the uneven defect can be detected more accurately.

(Embodiment 8)
The defect detection apparatus according to the eighth embodiment is different from the defect detection apparatus according to the first embodiment (see FIG. 1) in that the irradiation apparatus 1 irradiates the inspection surface B with diffused light. Hereinafter, the defect detection apparatus of the present embodiment will be described with reference to FIG. Note that the description of the same components as those in the first embodiment is omitted.

  By irradiating the diffused light with the defect, a bright and dark portion is likely to be generated in the defect. However, the diffused light may be insufficient depending on the defect shape and the surface state of the inspection target A.

  Therefore, the irradiation apparatus 1 of this embodiment includes a diffusion plate 11 as shown in FIG. By making the irradiation light itself of the irradiation apparatus 1 into diffused light, more diffused light is irradiated onto the defect.

  As described above, according to the defect detection apparatus of this embodiment, even when diffused light cannot be sufficiently obtained due to the state of the surface B to be inspected, the necessary diffused light can be supplied to the diffused light irradiation area D. It can be detected accurately.

(Embodiment 9)
The defect detection apparatus according to the ninth embodiment is different from the defect detection apparatus according to the first embodiment in that the amount of irradiation light is changed. Hereinafter, the defect detection apparatus of this embodiment will be described with reference to FIGS. In addition, about the component similar to Embodiment 1, the same code | symbol is attached | subjected and description is abbreviate | omitted.

  If the irradiation light from the irradiation device 1 is too strong, a saturation in which the luminance is saturated directly occurs in the area of the irradiation area C in the captured image, and if the unevenness amount is small, a minute black area generated in the area is buried. Therefore, there is a case where a minute region cannot be detected. In other words, the bright and dark areas of the defect may not be clear, or the area may be smaller than when no saturation occurs.

  Therefore, the defect detection apparatus according to the present embodiment includes polarizing filters 7 and 8 as a light amount adjustment unit as shown in FIG. The polarizing filters 7 and 8 reduce the amount of light incident on the imaging device 2. The polarizing filter 7 adjusts the polarization direction to the line direction of the irradiation light of the irradiation device 1, and the polarizing filter 8 adjusts the polarization direction so as to be inclined by 10 degrees with respect to the polarization direction of the polarizing filter 7. In this embodiment, the polarization filters 7 and 8 are applied to prevent the occurrence of saturation, and the minute area can be detected without the minute area in the direct irradiation area C being buried.

  As described above, according to the defect detection apparatus of the present embodiment, even when the reflected light is overdetected depending on the state of the inspection surface B and the defect cannot be detected from the captured image, the polarization filters 7 and 8 (light amount adjustment). Part), the amount of light incident on the imaging device 2 can be adjusted appropriately, so that defects can be detected more accurately.

  The polarizing filters 7 and 8 are an example, and the angles of the polarizing filters 7 and 8 are also an example. Further, the same effect can be obtained even if a polarizing filter is provided in either one of the irradiation device 1 and the imaging device 2.

  In addition, each function of the defect detection apparatus of Embodiments 1-9 can be used in combination as appropriate.

DESCRIPTION OF SYMBOLS 1 Irradiation device 11 Diffusion plate 2 Imaging device 3 Processing device 4 Transfer device 5 Input device (type input device, unevenness amount input device)
6 Driving device 7, 8 Polarizing filter (light quantity adjustment unit)
A Inspection object B Surface to be inspected C Direct irradiation area D Diffuse light irradiation area E Defect

Claims (10)

An irradiation device for irradiating light from an oblique direction onto a surface to be inspected having diffuse reflectivity; and
An imaging device for imaging the surface to be inspected that is irradiated with light from the irradiation device;
A processing device that detects a defect related to the unevenness of the surface to be inspected using a captured image captured by the imaging device;
A range in which the irradiation light of the irradiation device is directly irradiated on the surface to be inspected is a direct irradiation area, and a range in which diffused light generated by diffusion of the irradiation light in the direct irradiation area is irradiated on the surface to be inspected. As a diffused light irradiation area,
The imaging device is arranged to include the direct irradiation area and the diffused light irradiation area in an imaging region,
The processor is
The set of the second inspection region in the diffused light irradiation area, Luminance information of the first test area and the second inspection region sets a first inspection region in the direct illumination area in the captured image In order to detect the defect using
An extraction function for extracting a region having a lower brightness than the surroundings in the direct irradiation area and a region having a higher brightness than the surroundings in the diffused light irradiation area as defect candidate regions,
A defect detection apparatus comprising: a determination function that determines that the defect exists in the defect candidate region when the size of the defect candidate region is larger than a preset threshold value . An irradiation device for irradiating light from an oblique direction onto a surface to be inspected having diffuse reflectivity; and
An imaging device for imaging the surface to be inspected that is irradiated with light from the irradiation device;
A processing device that detects a defect related to the unevenness of the surface to be inspected using a captured image captured by the imaging device;
A range in which the irradiation light of the irradiation device is directly irradiated on the surface to be inspected is a direct irradiation area, and a range in which diffused light generated by diffusion of the irradiation light in the direct irradiation area is irradiated on the surface to be inspected. As a diffused light irradiation area,
The imaging device is arranged to include the direct irradiation area and the diffused light irradiation area in an imaging region,
The processor is
In the captured image, a first inspection area is set in the direct irradiation area, a second inspection area is set in the diffused light irradiation area, and luminance information of the first inspection area and the second inspection area is obtained. In order to detect the defect using
A first extraction function for extracting, as a first region, a region having a lower luminance than the surroundings in the direct irradiation area, and extracting a region having a higher luminance than the surroundings as a second region in the diffused light irradiation area;
An average brightness of a first setting area including the first area and having a preset size and an average brightness of a second setting area including the second area and having a preset size are calculated. A first calculation function;
A second calculation function for obtaining a binarization threshold value using the average luminance for each of the direct irradiation area and the diffused light irradiation area;
A second extraction function for performing a binarization process using the binarization threshold for each of the direct irradiation area and the diffused light irradiation area to extract a defect candidate area;
Defect detecting device you; and a determining function and size of the defect candidate area exists is the defect in the defect candidate region is greater than a preset threshold. In the second extraction function, when at least one of the first region and the second region is not extracted as the defect candidate region, the processing apparatus changes the binarization threshold value again. The defect detection apparatus according to claim 2, wherein binarization processing is performed to re-extract the defect candidate area . A type input device for inputting the type of the defect,
The processing device selects an inspection region used for detection of the defect from the first inspection region and the second inspection region according to the type input by the type input device. The defect detection apparatus according to any one of claims 1 to 3. A transport device for transporting the inspection object;
The imaging apparatus includes a timing at which a predetermined portion of the surface to be inspected reaches the direct irradiation area and a timing at which the predetermined portion reaches the diffused light irradiation area when the inspection target is transferred by the transfer device. Image
The processing device detects the defect using a captured image when the predetermined portion reaches the direct irradiation area and a captured image when the predetermined portion reaches the diffused light irradiation area. The defect detection apparatus according to any one of claims 1 to 3 . An unevenness input device for inputting the unevenness amount of the defect;
A driving device that varies the distance on the optical axis between the irradiation device and the surface to be inspected according to the unevenness amount input by the unevenness input device;
The imaging apparatus, in any one of claim 1 5, the distance on the optical axis is characterized in that imaging the inspected surface after being variable between the irradiation device and the surface to be inspected The defect detection apparatus described. The defect detection apparatus according to claim 1 , wherein the irradiation apparatus irradiates the surface to be inspected with diffused light . The defect detection device according to claim 1, further comprising a light amount adjustment unit that reduces a light amount of light incident on the imaging device. A first step of irradiating light from an oblique direction onto a surface to be inspected having diffuse reflectivity;
A second step of imaging the surface to be inspected;
A third step of detecting a defect related to the unevenness of the surface to be inspected using the captured image captured in the second step,
A range in which the irradiation light is directly irradiated on the surface to be inspected is a direct irradiation area, and a range in which the diffusion light generated by diffusion of the irradiation light in the direct irradiation area is irradiated on the surface to be inspected is a diffusion light irradiation area. age,
In the second step, imaging is performed so as to include the direct irradiation area and the diffused light irradiation area in an imaging region,
In the third step,
In the captured image, set a first inspection area in the direct irradiation area and set a second inspection area in the diffused light irradiation area,
Using the luminance information of the first inspection area and the second inspection area, a defect candidate is defined as an area having lower luminance than the surrounding area in the direct irradiation area and an area having higher luminance than the surrounding area in the diffused light irradiation area. Extract as a region,
A defect detection method comprising: determining that the defect exists in the defect candidate area when the size of the defect candidate area is larger than a preset threshold value, and detecting the defect . A first step of irradiating light from an oblique direction onto a surface to be inspected having diffuse reflectivity;
A second step of imaging the surface to be inspected;
A third step of detecting a defect related to the unevenness of the surface to be inspected using the captured image captured in the second step,
A range in which the irradiation light is directly irradiated on the surface to be inspected is a direct irradiation area, and a range in which the diffusion light generated by diffusion of the irradiation light in the direct irradiation area is irradiated on the surface to be inspected is a diffusion light irradiation area. age,
In the second step, imaging is performed so as to include the direct irradiation area and the diffused light irradiation area in an imaging region,
In the third step,
In the captured image, set a first inspection area in the direct irradiation area and set a second inspection area in the diffused light irradiation area,
Using Luminance information of the first test area and the second inspection area, said extracting region lower brightness than the surrounding in the direct radiation area as the first area, around in the diffused light irradiation area Extract a region with higher brightness as the second region,
An average brightness of a first setting area including the first area and having a preset size and an average brightness of a second setting area including the second area and having a preset size are calculated. ,
For each of the direct irradiation area and the diffused light irradiation area, a binary threshold value is obtained using the average luminance,
For each of the direct irradiation area and the diffused light irradiation area, binarization processing is performed using the binarization threshold value to extract a defect candidate area,
A defect detection method comprising: determining that the defect exists in the defect candidate region when the size of the defect candidate region is larger than a preset threshold value, and detecting the defect.