JP5402182B2 - Appearance inspection method and appearance inspection apparatus - Google Patents

Description

  The present invention relates to an appearance inspection method and an appearance inspection apparatus for inspecting the appearance of an inspection object.

  Conventionally, there is known an appearance inspection method for determining whether or not a defect exists in an inspection object by imaging the inspection object and performing predetermined image processing on the image data (for example, See Patent Document 1 below). Specifically, the appearance inspection method of Patent Document 1 includes a step of calculating an average luminance distribution of an inspection object in each of the X direction and the Y direction, a captured image, and a master image generated based on each average luminance distribution. Generating a first correction image from the first correction image, generating a Sobel processing image from the first correction image using a Sobel filter, and generating a second correction image from the Sobel processing image and the first correction image. And a step of binarizing the second corrected image to identify a connected area, and comparing the number of pixels in the connected area with a threshold value. As described above, it is conventionally known to correct the influence of luminance unevenness caused by the curved surface shape of an inspection object (so-called shading correction).

JP 2007-0785540 A (Patent No. 4150390)

  In Patent Document 1, a magnet having a cylindrical outer peripheral surface is used as an inspection target, and the outer peripheral surface is illuminated and the reflected light is captured by a camera to obtain a captured image. For this reason, in the captured image, the central portion of the magnet is projected brightly (luminance value: large), and both side portions of the magnet are projected darkly (luminance value: small).

  By the way, if there are defects such as chips or cracks in the inspection object, the reflected light often does not go to the camera even if the defect is illuminated, so the defect that appears in the captured image becomes dark. Easy (luminance value: small). Therefore, if there is a defect in the central part of the magnet, the brightness difference between the defect and the other part (also called brightness difference or contrast) becomes clear, but there is a defect on both sides of the magnet. In such a case, the luminance difference between the defect and the other part tends to be small. Therefore, there is a tendency that it is difficult to detect a defect existing in a dark part.

  Accordingly, an object of the present invention is to provide an appearance inspection method and an appearance inspection apparatus capable of accurately and reliably detecting a defect even when the defect exists in a dark part.

An appearance inspection method according to the present invention is an appearance inspection method for performing an appearance inspection of an inspection object, and includes a step of imaging the inspection object and obtaining a captured image including the inspection object image; Of the steps of determining the processing area to be subjected to the appearance inspection process, and the first to Kth sections (K is a natural number of 2 or more) that are set in the processing area and divide the processing area, the kth ( k is a natural number of 1 to K), the step of calculating the k-th average luminance value MBk, which is the average value of the luminance values of each pixel, and the largest value among the first to K-th average luminance values Is selected as the maximum value MBmax, and the luminance value of each pixel included in the kth section is expressed by the following equation (1).
Ik (x, y) × MBmax / MBk (1)
(However, Ik (x, y) represents a luminance value of a pixel at an arbitrary coordinate (x, y) included in the kth section.)
Each of the first pixel columns including a series of pixels parallel to the first direction along the outer edge of the replacement image, and a step of generating a replacement image by replacing each of the values obtained by And calculating the average of the luminance values of a series of pixels included in the second pixel column for each second pixel column consisting of a series of pixels parallel to a second direction orthogonal to the first direction. Calculating the average luminance distribution of the replacement image in the first direction and the second direction by calculating the average of the luminance values of the series of pixels, and calculating the average luminance of the reference image as a reference for the replacement image It has the process of producing | generating based on distribution, and the process of carrying out the shading correction | amendment of the captured image using a reference | standard image, It is characterized by the above-mentioned.

  In the appearance inspection method according to the present invention, a processing area to be subjected to appearance inspection processing in a captured image is divided into first to Kth sections. Then, the kth average luminance value Bk, which is the average value of the luminance values of the pixels included in the kth section, is calculated, and the largest value among the first to Kth average luminance values is selected as the maximum value MBmax. doing. Therefore, the average luminance value MBk decreases as each pixel included in the kth section is darker (luminance value: small), and the average luminance value MBk decreases as each pixel included in the kth section is brighter (luminance value: large). Therefore, the coefficient MBmax / MBk in the above formula (1) has a larger value for a generally dark section and a value closer to 1 for a generally bright section (MBmax / MBk ≧ 1). . Therefore, by performing the calculation according to the above equation (1) in all the sections, the luminance values of the pixels constituting the generally dark section of the inspection object image in the processing region are all bright sections. It is replaced with the same size as the luminance value of the constituent pixels. That is, since the entire dark section is brightened as a whole, even if the defect exists in the dark part, the brightness difference between the defect and the other part in the replacement image becomes clear. As a result, it is possible to detect a defect accurately and reliably by generating a reference image from the replacement image and using the reference image to perform shading correction of the captured image.

  Preferably, the sections are set so as to be arranged along a direction in which a change in luminance value is large in the inspection object image in the processing region. In this way, the luminance values of the pixels included in the section are uniform to some extent for each section (the same brightness distribution is obtained for each section). That is, in the inspection object image in the processing area, the dark part and the bright part are clearly divided, and the possibility that both the dark part and the bright part exist in the same section is reduced. Therefore, the luminance value of the dark part of the inspection object image in the processing region is amplified with high gain by the coefficient MBmax / MBk in the above equation (1). As a result, the brightness difference between the defect and the other part in the replacement image can be made clearer.

On the other hand, an appearance inspection apparatus according to the present invention is an appearance inspection apparatus for performing an appearance inspection of an inspection object, and illuminates an inspection object and illuminates the inspection object illuminated by the illumination means. An imaging unit that obtains a captured image including an inspection object image, a unit that determines a processing region to be subjected to an appearance inspection process in the captured image captured by the imaging unit, and is set in the processing region Of the first to Kth sections (K is a natural number of 2 or more) that divides the processing area, the brightness value of each pixel included in the kth section (k is a natural number of 1 to K) is the average value. means for calculating an average luminance value MBk of k, means for selecting the largest value among the first to Kth average luminance values as the maximum value MBmax, and the luminance value of each pixel included in the kth section, The following formula (2)
Ik (x, y) × MBmax / MBk (2)
(However, Ik (x, y) represents a luminance value of a pixel at an arbitrary coordinate (x, y) included in the kth section.)
Means for generating a replacement image by substituting each of the values obtained by the above, and for each first pixel column comprising a series of pixels parallel to the first direction along the outer edge of the replacement image, the first pixel column And calculating the average of the luminance values of a series of pixels included in the second pixel column for each second pixel column consisting of a series of pixels parallel to a second direction orthogonal to the first direction. Means for calculating an average luminance distribution of the replacement image in the first direction and the second direction by calculating an average of the luminance values of the series of pixels, and an average luminance of the reference image serving as a reference for the replacement image It has the means to produce | generate based on distribution, and the means to carry out the shading correction | amendment of the captured image using a reference | standard image, It is characterized by the above-mentioned.

  In the appearance inspection apparatus according to the present invention, a processing area to be subjected to appearance inspection processing in a captured image is divided into first to Kth sections. Then, the kth average luminance value MBk, which is the average value of the luminance values of the pixels included in the kth section, is calculated, and the largest value among the first to Kth average luminance values is selected as the maximum value MBmax. doing. Therefore, the average luminance value MBk decreases as each pixel included in the kth section is darker (luminance value: small), and the average luminance value MBk decreases as each pixel included in the kth section is brighter (luminance value: large). Therefore, the coefficient MBmax / MBk in the above equation (2) becomes a larger value as the overall dark section becomes closer to 1 as the overall bright section (MBmax / MBk ≧ 1). . Therefore, by performing the calculation according to the above equation (2) in all the sections, the luminance value of the pixels constituting the entire dark section of the inspection object image in the processing region is the entire bright section. It is replaced with the same size as the luminance value of the constituent pixels. That is, since the entire dark section is brightened as a whole, even if the defect exists in the dark part, the brightness difference between the defect and the other part in the replacement image becomes clear. As a result, it is possible to detect a defect accurately and reliably by generating a reference image from the replacement image and using the reference image to perform shading correction of the captured image.

  Preferably, the sections are set so as to be arranged along a direction in which a change in luminance value is large in the inspection object image in the processing region. In this way, the luminance values of the pixels included in the section are uniform to some extent for each section (the same brightness distribution is obtained for each section). That is, in the inspection object image in the processing area, the dark part and the bright part are clearly divided, and the possibility that both the dark part and the bright part exist in the same section is reduced. Accordingly, the luminance value of the dark part of the inspection object image in the processing region is amplified with high gain by the coefficient MBmax / MBk in the above equation (2). As a result, the brightness difference between the defect and the other part in the replacement image can be made clearer.

  ADVANTAGE OF THE INVENTION According to this invention, even if a defect exists in a dark part, the external appearance inspection method and external appearance inspection apparatus which can detect a defect accurately and reliably can be provided.

FIG. 1A is a perspective view schematically showing a configuration of an appearance inspection apparatus, and FIG. 1B is a perspective view of an inspection object. FIG. 2 is a flowchart showing a procedure from the start to the end of the appearance inspection process. FIG. 3 is a flowchart showing a procedure from the start to the end of the corrected image creation process. FIG. 4 is a flowchart showing a procedure from the start to the end of the first defect detection process. FIG. 5 is a flowchart showing a procedure from the start to the end of the second defect detection process. FIG. 6 is a flowchart showing a procedure from the start to the end of the third defect detection process. FIG. 7 shows each image in the first corrected image generation processing, FIG. 7A is a diagram showing a captured image, FIG. 7B is a diagram showing a replacement image, and FIG. FIG. 7C is a diagram showing a master image, and FIG. 7D is a diagram showing a first corrected image. FIG. 8A is a diagram showing an inspection object image for explaining a method of calculating the average luminance value, and FIG. 8B is a diagram showing a distribution of average luminance values in the axis X direction. FIG. 8C is a diagram showing a distribution of average luminance values in the axis Y direction. FIG. 9 is a diagram for explaining a method of generating a replacement image. FIG. 9A is a diagram illustrating an inspection object image in which a plurality of regions are set as processing regions. FIG. 9B is a diagram showing a distribution of luminance values along the line BB in FIG. 9A, and FIG. 9C is a diagram showing the BB in FIG. 9A after the contrast enhancement processing. It is a figure which shows distribution of the luminance value in a line. 10A and 10B show images in the defect detection first process, FIG. 10A shows a Sobel processed image, FIG. 10B shows a second corrected image, and FIG. FIG. 10C is a diagram showing a binarized image, and FIG. 10D is a diagram showing a defect detection result image. 11 shows each image in the defect detection second process, FIG. 11A shows the first corrected image, FIG. 11B shows the differential process image, and FIG. (C) of FIG. 11 is a diagram showing a third corrected image, (d) of FIG. 11 is a diagram showing a binarized image, and (e) of FIG. 11 is a diagram showing a defect detection result image. FIG. 12 shows each image in the third defect detection process, FIG. 12A shows a captured image, and FIG. 12B shows a binarized image. FIG. 13 is a diagram illustrating an inspection object image in which a plurality of areas are set as processing areas when the inspection object is an element body of a chip-type electronic component.

  A preferred embodiment of an appearance inspection apparatus 10 according to the present invention will be described with reference to the drawings. In the description, the same reference numerals are used for the same elements or elements having the same function, and a duplicate description is omitted.

(Configuration of appearance inspection equipment)
With reference to FIG. 1, the structure of the external appearance inspection apparatus 10 which concerns on this embodiment is demonstrated.

  The appearance inspection apparatus 10 is an apparatus for inspecting the appearance of an inspection object 22 to be described later. For this purpose, the appearance inspection apparatus 10 includes a camera 12, an image processing unit 14, a display 16, and LED illuminators 18a and 18b (see (a) of FIG. 1).

  The camera 12 images the outer surface of the inspection object 22 illuminated by the LED illuminators 18a and 18b. For example, a CCD (Charge Coupled Device) camera can be used. When the camera 12 acquires the captured images P1 and P13 (see FIG. 7A and FIG. 12A) of the inspection target 22, the data of the captured image P1 is output to the image processing unit 14. The camera 12 may be a CMOS (Complementary Metal Oxide Semiconductor) camera, an infrared camera, a black and white camera, a color camera, or the like, as long as it can obtain at least luminance information.

  The image processing unit 14 includes an unillustrated ECU (Electronic Control Unit) including a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), and the like. Image processing is performed. When the image processing unit 14 performs image processing on the captured images P1, P13, and the like, the image processing unit 14 outputs an image signal to the display 16 so that the processed image is displayed on the display 16.

  The display 16 displays various images such as captured images P1 and P13, a first corrected image P3 described later, and the presence or absence of defects. Therefore, the appearance of the inspection object 22 can be inspected by human eyes by observing various images displayed on the display 16 by the operator.

  The LED illuminators 18a and 18b are ring-shaped lighting fixtures that can illuminate the inspection object 22 from the direction of 360 ° around the LED illuminators 18a and 18b, and the inspection object 22 is placed above the inspection object 22. Each is provided so as to face the plate 20. The LED illuminator 18a is disposed on the mounting plate 20 side, has a substantially cylindrical shape, and a plurality of LED light sources are arranged on the inner surface thereof. For this reason, the LED illuminator 18a illuminates from the inner side surface toward the center of the LED illuminator 18a. On the other hand, the LED illuminator 18b is disposed on the camera 12 side, and has an inner surface of a substantially conical shape, and a plurality of LED light sources are arranged on the inner surface. For this reason, the LED illuminator 18b illuminates downward from the inner surface with a predetermined angle. By using these LED illuminators 18a and 18b, the inspection object 22 is uniformly illuminated.

  Here, in this embodiment, the inspection object 22 has an outer peripheral surface 22a and an inner peripheral surface 22b that are formed into cylindrical surfaces, and the side surface 22c has an arc shape ((b) in FIG. 1). reference). The outer peripheral surface 22a and the inner peripheral surface 22b of the inspection object 22 are in the axial direction of the outer peripheral surface 22a and the inner peripheral surface 22b that form a cylindrical surface in the process of manufacturing the inspection object 22, and each inspection object Different polishing streaks are formed for each object 22. The inspection object 22 is used as a magnet for a motor such as a cooler, for example.

  Examples of defects that can occur in the inspection object 22 include cracks, chips, and peeling. A crack has a relatively small size (area) compared to other defects. Since the crack has a deep defect depth (defect depth) from the surface of the inspection object 22, the amount of change in the luminance value in the defect portion of the captured image tends to be a large value. The chipping can occur from a small to a large defect size (area). Since the defect has a defect depth from a shallow depth to a deep depth, the amount of change in the luminance value in the defective portion of the captured image can take a small value to a large value. In peeling, the size (area) of defects is relatively large. In peeling, since the defect depth is relatively shallow, the amount of change in the luminance value in the defective portion of the captured image tends to be a small value.

(Appearance inspection method using appearance inspection equipment)
Next, with reference to FIGS. 2 to 12, an appearance inspection processing method for the inspection object 22 using the appearance inspection apparatus 10 having the above configuration will be described. Here, in particular, a case will be described in which an appearance inspection is performed on the outer peripheral surface 22a or the inner peripheral surface 22b having a cylindrical surface shape in the inspection object 22. In the flowcharts shown in FIGS. 2 to 6, the step is abbreviated as S. 7, 11, and 12, the defect detection first process, the defect detection second process, and the defect detection third process are described using different inspection objects 22.

  When the appearance inspection process is started by the appearance inspection apparatus 10, the process proceeds to Step 1 shown in FIG. 2, and the inspection object 22 is positioned by the operator of the appearance inspection apparatus 20. Specifically, by pressing the inspection object 22 against a pin (not shown) provided on the mounting plate 20 with a spring, the polishing streaks of the inspection object 22 become short sides (in the inspection object image P1a). The inspection object 22 is fixed to the mounting plate 20 along the axis Y direction shown in FIG. In this way, the outer edges of the captured image P1 and the image (inspection object image) P1a indicating the inspection object 22 in the captured image P1 are parallel, and a first corrected image P3 described later can be easily obtained from the captured image P1. Become.

  Subsequently, when proceeding to Step 2, the inspection object 22 illuminated by the LED illuminators 18a and 18b is imaged by the camera 12 (see FIG. 7A). When the inspection object 22 is imaged by the camera 12, data of the captured image P <b> 1 is output to the image processing unit 14. In the first corrected image generation process, the defect detection first process, the defect detection second process, and the defect detection third process described below, the defect of the inspection target 22 is detected by the image processing unit 14 based on the data of the captured image P1. Various processes are performed for this purpose.

(First corrected image generation process)
In the subsequent step 3, a first corrected image generation process is performed. When the first corrected image generation process is started, the process proceeds to step 11 shown in FIG. 3, and after obtaining a region of continuous pixels whose luminance value is not 0 in the captured image P <b> 1, a rectangle circumscribing the region of the pixel Is obtained to determine the outer shape area A1 of the inspection object image P1a in the captured image P1. At this time, a process of calculating the determined area (number of pixels) of the outer region A1 and the coordinates where the outer region A1 is located is also performed. In step 12, it is determined whether or not the area of the outer shape area A1 determined in step 11 is equal to or larger than a predetermined threshold value. That is, since the area (number of pixels) of the inspection object image P1a that is a target for detecting a defect is substantially the same in each inspection object 22, imaging is performed if the area (number of pixels) of the outer region A1 is equal to or greater than the threshold value. If it is determined that the object to be inspected is the inspection object 22 and the process proceeds to step 13, otherwise, it is determined that the imaged object is not the inspection object 22 (for example, a fragment of the inspection object 22). The process proceeds to step 8 shown in FIG. 2 to end the appearance inspection process.

In step 13, an area (processing area) A2 to be processed in the captured image P1 is determined based on the outer area A1. The processing for determining the processing area A2 will be specifically described below with reference to FIG. In addition, in the outer area A1 shown in FIG. 8A, each rectangular area surrounded by a white solid line grid corresponds to a pixel (for the sake of illustration, the size is exaggerated from the actual size). The coordinates of the pixels along the axis X direction parallel to the long side are 1 to x _max , and the coordinates of the pixels along the axis Y direction parallel to the short side and orthogonal to the axis X are 1 to y _max. ing. In addition, the luminance value of a pixel at an arbitrary coordinate (x, y) in the outer region A1 is represented as I (x, y).

When determining the processing area A2, first, the average (average luminance value) Y of the luminance values I (1, y) to I (x _max , y) for a series of pixels parallel to the axis X direction is calculated in the axis Y direction. Calculate every time. Further, an average (average luminance value) X of the luminance values I (x, 1) to I (x, y _max ) for a series of pixels parallel to the axis Y direction is calculated for each axis X direction. The average luminance distributions L1 and L2 shown in FIGS. 8B and 8C represent changes in the average luminance values X and Y calculated in this way, respectively. The average luminance value Yn when the Y coordinate is n is expressed by the following equation (3), and the average luminance value Xm when the X coordinate is m is expressed by the following equation (4).


After obtaining these average luminance values X and Y, the threshold values indicated by the broken lines in FIGS. 8B and 8C are compared with the average luminance values X and Y, respectively, and the average luminance value X equal to the threshold value is compared. , Y indicating x and y coordinates respectively. Then, a region that passes through the coordinates thus obtained and is surrounded by a straight line perpendicular to the axis X or the axis Y where the coordinates exist is determined as the processing region A2. The processing area A2 may be determined by dividing the outer area A1 into a plurality of areas and obtaining an average luminance value for each area.

  Subsequently, when proceeding to step 14, contrast enhancement processing is performed on the captured image P1 (inspection object image P1a) in the processing area A2 to generate a replacement image Pr. When generating the replacement image Pr, first, the rectangular processing area A2 is divided into a plurality of rectangular sections B1 to BK (K is a natural number of 2 or more) (in the present embodiment, 9 of the sections B1 to B9). (Refer to FIG. 9A). In the present embodiment, the sections B1 to B9 are set so as to be aligned along the longitudinal direction of the processing area A2.

  Here, the inspection object 22 of the present embodiment has an outer peripheral surface 22a having a cylindrical surface shape. For this reason, in the captured image P1 in FIG. 9A, the central portion is projected brightly, and the left and right side portions are projected darkly, while the change in luminance value is small in the vertical direction. That is, it can be said that the sections B1 to B9 are set so as to be arranged along the direction in which the change in the luminance value is large in the inspection object image P1a in the processing area A2. Note that the appearance inspection apparatus 10 according to the present embodiment aims to inspect a large number of inspection objects 22 having the same shape, and it is expected that any captured image will be similar as long as there is no defect. Therefore, a plurality of sections may be set in advance prior to the inspection of the inspection object 22, or the sections may be reset for each inspection object 22.

Next, an average luminance value MB, which is an average value of the luminance values of all the pixels in the section, is calculated for all the sections. That is, when there are sections B1 to BK, the luminance value of a pixel at an arbitrary coordinate (x, y) in the section Bk (k is a natural number of 1 to K) is expressed as Ik (x, y). The average luminance value MBk of k is calculated by the following equation (5). In the present embodiment, since there are nine sections B1 to B9, the average luminance values MB1 to MB9 for the sections B1 to B9 are calculated.

Next, the largest value (maximum value MBmax) among the average luminance values MB1 to MBK (MB1 to MB9 in the present embodiment) is calculated by the following equation (6).
MBmax = max (MB1, MB2,..., MBK) (6)
(Max (argument 1, argument 2,...) Represents a function that returns the largest argument among argument 1, argument 2,...)
In the present embodiment, since the section B5 is brightest (see FIG. 9A), the average luminance value MB5 becomes the maximum value MBmax (MBmax = MB5).

Next, the luminance value of each pixel included in the section Bk is expressed by the following equation (7).
Ik (x, y) × MBmax / MBk (7)
The replacement process is performed in all the sections B1 to BK with the values obtained by the above steps, and the replacement image Pr is generated. Here, from the above equation (6), since MBmax / MBk ≧ 1, the above equation (7) expresses the luminance value Ik (x, y) of each pixel included in the section Bk as the coefficient MBmax / MBk. Means to amplify. As an example, FIG. 9B shows the distribution of luminance values before the calculation according to the above equation (7), and FIG. 9 shows the distribution of luminance values after the calculation according to the above equation (7). (C). As shown in (b) and (c) of FIG. 9, since the average luminance values MB2 and MB8 are small in the sections B2 and B8, the luminance value after the calculation of the above equation (7) is increased by the coefficient MBmax / MBk. On the other hand, since the average luminance value MB5 is the highest value MBmax in the section B5, the luminance value after the calculation of the above equation (7) is the same value as before the calculation.

Subsequently, when proceeding to Step 15, a master image (reference image) P2 is generated based on the replacement image Pr. When generating the master image P2, first, average luminance values X ′ and Y ′ are obtained again in the processing area A2 of the replacement image Pr. Based on these average luminance values X ′ and Y ′, the luminance value I ′ (m, n) of the pixel at the coordinates (m, n) is calculated for all the pixels in the processing area A2 from the following equation (8). A master image P2 is generated (see FIG. 7C).
Here, α and β in Expression (8) are the contribution ratios of the average luminance values in the directions of the axes X and Y, respectively. When generating the master image P2, the master image P2 to be generated can be adjusted by setting a larger value on the side of the contribution ratios α and β to be prioritized with respect to the average luminance values X ′ and Y ′. In the present embodiment, the value of α is made larger than β in order to take into account the influence of the polishing bars along the axis X direction.

  Subsequently, when proceeding to Step 16, for each pixel located at the corresponding coordinates in the inspection object image P1a and the master image P2 in the processing area A2, the master image P2 is calculated from the luminance value in each pixel of the inspection object image P1a. The luminance value at each pixel is subtracted. Thereby, the 1st correction image P3 is produced | generated (refer (d) of FIG. 7), and a 1st correction image production | generation process is complete | finished.

(Defect detection first process)
Returning to FIG. 2 and proceeding to step 4, the first defect detection process is performed. In this defect detection first process, for example, a defect due to a crack in the inspection object 22 or a foreign substance attached to the inspection object 22 is detected. When the first defect detection process is started, the process proceeds to step 21 shown in FIG. 4, where the first corrected image P3 is processed by the Sobel filter in the processing area A2, and the change in density (edge) in the first corrected image P3 is processed. (Part) is detected. Specifically, the calculation according to the following equation (9) is performed for all the pixels of the first corrected image P3 with a predetermined pixel in the first corrected image P3 and adjacent pixels around the pixel. As a result, a change amount E1 of the luminance value I ′ of each pixel in the first corrected image P3 is obtained, and a Sobel processed image P4 is generated in which the edge is detected at the portion where the shade change occurs (FIG. 10). (See (a)).
In addition, after generating the Sobel processed image P4, the calculation according to the following equation (10) is performed for all the pixels of the Sobel processed image P4 with a predetermined pixel in the Sobel processed image P4 and adjacent pixels around the pixel. Thereby, the average M1 of the luminance values I ′ of each pixel in the Sobel processed image P4 is obtained, and smoothing is performed to remove random noise generated in the Sobel processed image P4.
In the present embodiment, since the gradation is set to 256 gradations (8 bits), when the change amount E1 is obtained, if the change amount E1 falls below the lower limit of 0, the change amount E1 is the lower limit value. When the change amount E1 exceeds the upper limit value of 255, the change amount E1 is fixed to 255, which is the upper limit value. However, the same processing is performed with gradations other than 256 gradations. You may go.

  Subsequently, when proceeding to step 22, for each pixel located at the corresponding coordinates in the first corrected image P3 and the Sobel processed image P4 in the processing area A2, the Sobel processed image is calculated from the luminance value in each pixel of the first corrected image P3. The luminance value in each pixel of P4 is subtracted. Thereby, the 2nd correction image P5 is produced | generated (refer FIG.10 (b)). Further, after generating the second corrected image P5, the second corrected image P5 is smoothed in the same manner as in step 21 in order to remove random noise generated in the second corrected image P5.

  Subsequently, when proceeding to Step 23, the obtained second corrected image P5 is binarized by a predetermined threshold value, pixels having a luminance value equal to or higher than the threshold value are black, and pixels having a luminance value smaller than the threshold value are selected. A binarized image P6 displayed as white is generated (see FIG. 10C). Here, the threshold value used in the binarization process in step 23 is a value obtained by conducting an experiment in advance (the threshold values used in steps 33 and 41 described later are also the same). In this embodiment, the threshold values in steps 23 and 33 are the same, and the threshold value in step 41 is larger than the threshold values in steps 23 and 33. This is because in the second and third corrected images before the binarization processing in steps 23 and 33, the luminance values in the regions other than the defective portion are substantially uniform by the Sobel filter and the differential filter. While the range in which the threshold can be set is wide, in the inspection object image P13a before the binarization processing in step 41, the luminance value in the region other than the defective portion is not substantially uniform, so the threshold is set. This is because the range that can be set is narrow. Then, when proceeding to step 24, the binarized image P6 is labeled, and a connected area where pixels displayed in white in the binarized image P6 are connected is specified. In step 24, processing is performed to detect the number of identified connected regions, the area (number of pixels) of each connected region, and the position of each connected region in the processing region A2.

  Subsequently, when proceeding to step 25, it is determined whether or not the area (number of pixels) of each connected region is smaller than a predetermined threshold for each connected region detected in step 24. As a result, if it is determined that the area of the connected region is smaller than the threshold value for all the connected regions, the first defect detection process ends. If not, the process proceeds to step 8 in FIG. It is determined that there is a defect in the inspection object 22 on which the inspection is performed, and the appearance inspection process is terminated. Here, the threshold value used in the determination of step 25 is also a value obtained by conducting an experiment in advance (the threshold values used in steps 35 and 43 described later are also the same). In this embodiment, the threshold values in steps 25 and 35 are the same, and the threshold value in step 43 is larger than the threshold values in steps 25 and 35. This is because the area (number of pixels) of the defect due to the crack that is the detection target in the defect detection first process and the defect that is the defect that is the detection target in the defect detection second process is the detection target in the defect detection third process. This is because the area (number of pixels) of the defect due to the peeling tends to be smaller. FIG. 10D shows each pixel of the inspection object image P1a and the binarized image for each pixel located at the corresponding coordinates in the inspection object image P1a and the binarized image P6 in the processing area A2. It is a defect detection result image P7 obtained by adding each pixel of P6.

(Defect detection second process)
Returning to FIG. 2 and proceeding to step 5, the second defect detection process is performed. In this defect detection first process, for example, a defect due to a chip of the inspection object 22 is detected. When the second defect detection process is started, the process proceeds to step 31 shown in FIG. 5, where the first correction image P8 (see FIG. 11A) is processed by the differential filter in the processing area A2, and the first correction is performed. Processing for detecting a change in shading (edge portion) in the image P8 is performed. Specifically, the calculation according to the following equation (11) is performed for all the pixels of the first corrected image P8 with a predetermined pixel in the first corrected image P8 and adjacent pixels around the pixel. As a result, a change amount E2 of the luminance value I ′ of each pixel in the first corrected image P8 is obtained, and a differentiated image P9 is generated in which the edge is detected at the portion where the shading change occurs (FIG. 11). (See (b)).
In addition, after generating the differential processing image P9, the calculation according to the following expression (12) is performed on all the pixels of the differential processing image P9 with a predetermined pixel in the differential processing image P9 and adjacent pixels around the pixel. Thereby, the average M2 of the luminance values I ′ of each pixel in the differential processing image P9 is obtained, and smoothing is performed to remove random noise generated in the differential processing image P9.
In the second defect detection process, the change amount E2 is fixed to the lower limit value when the change amount E2 is lower than the lower limit value, and the change amount E2 is fixed to the upper limit value when the change amount E2 exceeds the upper limit value. Processing to do.

  Subsequently, when the process proceeds to step 32, the luminance value and the differential processing image in each pixel of the first correction image P8 are determined for each pixel located at the corresponding coordinates in the processing area A2 in the first correction image P8 and the differential processing image P9. The luminance value in each pixel of P9 is added. Thereby, the 3rd correction image P10 is produced | generated (refer (c) of FIG. 11). Further, after the generation of the third corrected image P10, the third corrected image P10 is smoothed in the same manner as in step 21 in order to remove random noise generated in the third corrected image P10.

  Subsequently, when proceeding to Step 33, the obtained third corrected image P10 is binarized by a predetermined threshold value, pixels having a luminance value equal to or higher than the threshold value are white, and pixels having a luminance value smaller than the threshold value are selected. A binarized image P11 displayed as black is generated (see FIG. 11D). Then, when proceeding to step 34, the binarized image P11 is labeled, and a connected area where pixels displayed in white in the binarized image P11 are connected is specified. In step 34, processing is performed to detect the number of identified connected regions, the area (number of pixels) of each connected region, and the position of each connected region in the processing region A2.

  Subsequently, when proceeding to step 35, it is determined whether or not the area (number of pixels) of each connected region is smaller than a predetermined threshold for each connected region detected in step 34. As a result, if it is determined that the area of the connected area is smaller than the threshold value for all the connected areas, the second defect detection process ends. If not, the process proceeds to step 8 in FIG. It is determined that there is a defect in the inspection object 22 on which the inspection is performed, and the appearance inspection process is terminated. Note that (e) in FIG. 11 shows each pixel of the inspection object image and the binarized image for each pixel located at coordinates corresponding to the inspection object image (not shown) and the binarized image P11 in the processing area A2. It is a defect detection result image P12 obtained by adding each pixel of P11.

(Defect detection third process)
Returning to FIG. 2 and proceeding to step 6, a third defect detection process is performed. In the first defect detection process, for example, a defect due to peeling of the inspection object 22 is detected. When the third defect detection process is started, the process proceeds to step 41 shown in FIG. 6, where the inspection object image P13a in the processing area A2 is binarized by a predetermined threshold value, and the luminance value is equal to or higher than the threshold value. A binarized image P14 is generated in which the pixels are displayed as white and the pixels having a luminance value smaller than the threshold value are displayed as black (see FIG. 12B). Then, when proceeding to step 42, the binarized image P14 is labeled, and a connected region where pixels displayed in white in the binarized image P14 are connected is specified. In step 42, processing is performed to detect the number of identified connected regions, the area (number of pixels) of each connected region, and the position of each connected region in the processing region A2.

  Subsequently, when proceeding to step 43, it is determined whether or not the area (number of pixels) of each connected region is smaller than a predetermined threshold for each connected region detected in step 42. As a result, when it is determined that the area of the connected region is smaller than the threshold value for all the connected regions, the binarization process is completed, and the process proceeds to step 7 in FIG. It is determined that the object 22 is not defective, and the appearance inspection process is completed. On the other hand, if it is determined that the area of any of the connected regions is greater than or equal to the threshold, the process proceeds to step 8 in FIG. 2 to determine that the inspection object 22 currently undergoing visual inspection is defective. Then, the appearance inspection process ends.

  In the present embodiment as described above, the processing area A2 to be subjected to the appearance inspection process in the captured image P1 is divided into sections B1 to BK. Then, an average luminance value Bk that is an average value of the luminance values of the pixels included in the section Bk is calculated, and the largest value among the average luminance values B1 to BK is selected as the maximum value MBmax. Therefore, the average luminance value MBk decreases as the pixels included in the section Bk become darker (luminance value: small), and the average luminance value MBk increases as the pixels included in the section Bk become brighter (luminance value: large). Therefore, the coefficient MBmax / MBk in the above equation (7) becomes a larger value as the overall dark section becomes closer to 1 (MBmax / MBk ≧ 1) as the overall bright section. Therefore, by performing the calculation according to the above equation (7) in all the sections, the luminance value of the pixels constituting the entire dark section of the inspection object image in the processing region is the entire bright section. It is replaced with the same size as the luminance value of the constituent pixels. That is, since the entire dark section is brightened as a whole, even if the defect exists in the dark part, the brightness difference between the defect and the other part in the replacement image becomes clear. As a result, it is possible to detect a defect accurately and reliably by generating a reference image from the replacement image and using the reference image to perform shading correction of the captured image.

  Further, in the present embodiment, the sections B1 to BK are set so as to be arranged along the direction in which the change in the luminance value is large in the inspection object image in the processing region. In this way, the luminance values of the pixels included in the section are uniform to some extent for each section (the same brightness distribution is obtained for each section). That is, in the inspection object image P1a in the processing area A2, the dark part and the bright part are clearly divided, and the possibility that both the dark part and the bright part exist in the same section is reduced. Therefore, the luminance value of the dark part of the inspection object image P1a in the processing area A2 is amplified with high gain by the coefficient MBmax / MBk in the above equation (7). As a result, the brightness difference between the defect and the other portion in the replacement image Pr can be made clearer.

  Although the preferred embodiments of the present invention have been described in detail above, the present invention is not limited to the above-described embodiments. For example, in the present embodiment, the defect detection first to third processes are performed in the appearance inspection process, but only the defect detection first process may be performed among these processes. Further, the defect detection first and second processes may be performed, or the defect detection first and third processes may be performed. Furthermore, execution may be started from any of the processes of the defect detection first to third processes.

  In the present embodiment, the appearance inspection is performed on the inspection target 22 having a curved surface. However, the present invention is not limited to this, and the appearance inspection of a planar inspection target may be performed. Further, an appearance inspection may be performed by using a substantially rectangular parallelepiped-shaped electronic component (chip-type electronic component) such as a chip capacitor or a chip inductor or an element body thereof as an inspection object.

  Here, the chip-type electronic component is manufactured by baking the external electrode on the element body. Generally, the element body is subjected to barrel polishing before the external electrode is baked on the element body. The ridge is chamfered and rounded. For this reason, in the captured image obtained by imaging the element body, the side surface tends to appear brighter and the darker the image toward the ridge portion (see FIG. 13). Therefore, when the inspection object is a chip-type electronic component or its element body, it is preferable to divide the sections as shown in FIG.

  Specifically, in FIG. 13, the central portion of the side surface of the element body is defined as a section B1, the ridges on the right side of the drawing are defined as sections B2 and B3, and the ridges on the left side of the drawing are defined as sections B4 and B5. The sections are defined as sections B6 and B7, and the ridges on the lower side of the drawing are defined as sections B8 and B9. Therefore, when viewing the vertical direction in FIG. 13, the luminance values of the pixels are small, large, and small (that is, dark, bright, dark) in the order of the upper ridge, the center of the side of the element body, and the lower ridge. Therefore, it can be said that the sections B7, B6, B1, B8, and B9 are set so as to be aligned along the direction in which the change in the luminance value is large. Similarly, when viewing the horizontal direction in FIG. 13, the luminance values of the pixels are small, large, and small (that is, dark, bright, dark) in the order of the right ridge, the center of the side surface of the element body, and the left ridge. Therefore, it can be said that the sections B3, B2, B1, B4, and B5 are set so as to be arranged along the direction in which the change in luminance value is large.

  In step 11, the outer region A1 may be determined by searching for the edge of the inspection object image P1a from four directions.

DESCRIPTION OF SYMBOLS 10 ... Appearance inspection apparatus, 12 ... Camera, 14 ... Image processing part, 22 ... Inspection object, P1, P
13 ... Captured image, P1a, P13a ... Inspection object image, Pr ... Replacement image, P2 ... Master image, P3, P8 ... First corrected image, P4 ... Sobel processed image, P5 ... Second corrected image, P9 ... Differential processing Image, P10 ... third corrected image.

Claims (4)

An appearance inspection method for performing an appearance inspection of an inspection object,
Imaging the inspection object to obtain a captured image including the inspection object image;
Determining a processing region to be subjected to appearance inspection processing in the captured image;
Among the first to Kth (K is a natural number of 2 or more) sections that are set in the processing area and divide the processing area, they are included in the kth (k is a natural number of 1 to K) section. Calculating a k-th average luminance value MBk, which is an average value of the luminance values of each pixel;
Selecting the largest value among the first to Kth average luminance values as the highest value MBmax;
The luminance value of each pixel included in the kth section is expressed by the following equation (1).
Ik (x, y) × MBmax / MBk (1)
(However, Ik (x, y) represents a luminance value of a pixel at an arbitrary coordinate (x, y) included in the kth section.)
Generating a replacement image by replacing each with the value obtained by
Calculating an average of luminance values of the series of pixels included in the first pixel column for each first pixel column including a series of pixels parallel to a first direction along an outer edge of the replacement image; By calculating the average of the luminance values of the series of pixels included in the second pixel column for each second pixel column composed of a series of pixels parallel to the second direction orthogonal to the first direction, Calculating an average luminance distribution of the replacement image in the first direction and the second direction;
Generating a reference image serving as a reference for the replacement image based on the average luminance distribution;
And a step of shading correction of the captured image using the reference image.   The appearance inspection method according to claim 1, wherein the section is set so as to be arranged along a direction in which a change in luminance value is large in the inspection object image in the processing region. An appearance inspection apparatus for inspecting the appearance of an inspection object,
Illuminating means for illuminating the inspection object;
An imaging unit that captures an image of the inspection object illuminated by the illumination unit and obtains a captured image including the inspection object image;
Means for determining a processing region to be subjected to appearance inspection processing in the captured image captured by the imaging means;
Among the first to Kth (K is a natural number of 2 or more) sections that are set in the processing area and divide the processing area, they are included in the kth (k is a natural number of 1 to K) section. Means for calculating a k-th average luminance value MBk, which is an average value of luminance values of the respective pixels;
Means for selecting the largest value among the first to K-th average luminance values as the highest value MBmax;
The luminance value of each pixel included in the kth section is expressed by the following equation (2).
Ik (x, y) × MBmax / MBk (2)
(However, Ik (x, y) represents a luminance value of a pixel at an arbitrary coordinate (x, y) included in the kth section.)
Means for generating a replacement image by replacing each of the values obtained by
Calculating an average of luminance values of the series of pixels included in the first pixel column for each first pixel column including a series of pixels parallel to a first direction along an outer edge of the replacement image; By calculating the average of the luminance values of the series of pixels included in the second pixel column for each second pixel column composed of a series of pixels parallel to the second direction orthogonal to the first direction, Means for calculating an average luminance distribution of the replacement image in the first direction and the second direction;
Means for generating a reference image serving as a reference for the replacement image based on the average luminance distribution;
An appearance inspection apparatus comprising: means for shading correction of the captured image using the reference image.   The appearance inspection apparatus according to claim 3, wherein the section is set so as to be arranged along a direction in which a change in luminance value is large in the inspection object image in the processing region.