JP2000283930A - Surface inspection device and surface inspection method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a surface inspection device and a surface inspection method, capable of detecting highly precisely irregularities in a low contrast, and capable of executing accurately quality judgement of a work to be inspected. SOLUTION: In this surface inspection device and this surface inspection method, quality determination of a work to be inspected is executed by executing image processing of an image to be inspected. To put it concretely, an oblong region dividing part 40 divides a prescribed region of the image to be inspected and extracts plural oblong regions. A projection part 44 projects brightness values of each oblong region on a specific axis. A dispersion calculation part 46 calculates dispersion values based on the projected results. A quality determination part 48 executes quality determination of the work to be inspected by using the dispersion values in each oblong region as a reference.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a surface detecting element and a surface detecting method, and more particularly, to a surface inspecting apparatus and method for inspecting a photosensitive layer of a photosensitive drum.

[0002]

2. Description of the Related Art An outer peripheral surface of a photosensitive drum, for example, an OPC drum (OPC: organic photoconductor) is
A photosensitive layer is coated. If foreign matter adheres to the photosensitive layer, or if there is uneven coating on the photosensitive layer, image quality will be degraded. Accordingly, a defect inspection for inspecting the surface of the photosensitive drum (workpiece to be inspected) is performed in advance.

When foreign matter is adhered to the surface of the drum, when the surface of the drum is illuminated and diffusely reflected light is observed, a remarkable change in the brightness value of the density of the drum surface appears. On the other hand, in the case where there is uneven coating, when specularly reflected light due to illumination is observed, a slight change appears in the density brightness value of the drum surface.

Therefore, in the conventional inspection, various illuminations are applied to the drum, and the operator visually detects abnormalities such as unevenness in color and luminance change on the surface of the drum, and determines a good product based on experience.

On the other hand, an apparatus for automatically inspecting the OPC photosensitive drum for defects using optical means has been developed. FIG. 20 is a diagram for explaining a surface inspection unit for the photosensitive drum. In these automatic inspection means, the photosensitive drum 50, which is the work to be inspected, is rotated about a drum rotation shaft 56. Then, the photosensitive drum 50 is illuminated by the line-type illumination 52 arranged in parallel with the drum rotation axis 56, and the line sensor camera 54 captures the reflected light from the rotating drum. Then, the two-dimensional image acquired from the line sensor camera is compared with a preset light and shade threshold value to automatically determine a defect (uneven coating, scratch, foreign matter adhesion) on the photosensitive drum. Note that FIG.
A hatched portion on the surface of the photosensitive drum at 0 indicates uneven coating.

FIG. 21 shows an image obtained when the OPC photosensitive drum 50 shown in FIG. In FIG. 21, the X axis corresponds to the drum rotation axis 56, and the Y axis corresponds to the drum rotation direction. As shown in FIG. 21, in the image to be inspected photographed by an image sensor such as the line sensor camera 54, the central region D0
A shading phenomenon occurs in which the left and right regions D1 and D2 become black as compared with the case of FIG. In addition, when the line-type illumination 52 irradiated in the direction of the drum rotation axis 56 has uneven illuminance, light and shade (area D3) due to a decrease or increase in luminance occurs in the scanning direction (Y-axis direction). These irregularities extend in the Y-axis direction. On the other hand, the light and shade stripes due to uneven coating extend in the drum rotation axis direction (X-axis direction) because the drum is dipped in the liquid tank in the direction of the rotation axis to perform coating and causes liquid dripping. When this is photographed by an image sensor such as the line sensor camera 54, the brightness unevenness extends in the X-axis direction as shown in FIG. 21 (region D4).

FIG. 22 is a diagram showing a change in gray-scale luminance value on the line AA 'in FIG. FIG.
As shown in (1), generally, the luminance value tends to decrease from the center of the image toward the both ends. In particular, when there is uneven illumination, the luminance value drops sharply.

[0008] As one example of such an automatic inspection method, there is a "flaw inspection method (Japanese Patent Application No. 4-70553)". The inspection method includes a method of shading determined by a dark output of a light receiving unit that receives light irregularly reflected from a work to be inspected and a signal output of the light receiving unit by reflected light of the work to be inspected having a normal surface without defects. The defect determination is performed using a gray level threshold determined by the value from which the influence has been removed.

[0009] Further, "Surface inspection method (JP-A-4-273)
No. 046), the image to be inspected obtained by the imaging means is divided into a plurality of regions based on the magnitude of the luminance change, and the region having a large luminance change is reduced in luminance gradation to reduce the spatial resolution. Is set high, and in a region where the luminance change is small, the defect inspection is performed by setting the luminance gradation to be high and the spatial resolution to be low.

Further, in "Appearance inspection apparatus and inspection method for electrophotographic photoreceptor (Japanese Patent Laid-Open No. 9-196643)", an average gray-scale brightness value of an image obtained by a line sensor is obtained, and each pixel is obtained for each pixel. On the other hand, a method is disclosed in which a difference between the average value and the average value is determined, and a difference having a large difference is determined as defective.

[0011]

However, the above-mentioned conventional method has the following problems. First, with respect to the visual inspection, there is a tendency that the quality judgment criteria among the operators vary, and the quality is unstable. The throughput varies depending on the operator. Due to the fatigue of the worker caused by the long-time work, oversight of a defect, a change in a criterion, and the like occur.

Further, according to the conventional method of automatically inspecting using an optical method, it is necessary to repeatedly acquire data for calibration in order to remove the influence of uneven illumination and shading. Has a lot of hassle. In particular, if a method is used in which the spatial resolution is set low when the contrast is small, it becomes difficult to inspect small-sized spots. Further, as described above, when foreign matter is attached to the drum surface, a remarkable change appears in the grayscale luminance value. For example, in the case of uneven painting, the change in the grayscale luminance value is subtle. Therefore, if the pass / fail judgment is performed based on the shading threshold value, it is difficult to judge a low-contrast defective pattern as noise, and the reliability of the judgment decreases.

SUMMARY OF THE INVENTION The present invention has been made in order to solve the above-mentioned problem, and an object of the present invention is to provide a surface inspection apparatus and a surface inspection apparatus capable of automatically inspecting even a low-contrast defective pattern. It is to provide a method.

[0014]

According to a first aspect of the present invention, there is provided a surface inspection apparatus for determining the quality of a work to be inspected, wherein illumination of the work to be inspected is changed while changing a posture of the work to be inspected. Providing means, a photographing means for photographing the surface of the work to be inspected, and an image processing means for judging the quality of the work to be inspected based on the image to be inspected acquired by the photographing means. Area dividing means for dividing the target area of the image into a plurality of rectangular areas; projecting means for projecting the luminance value of each pixel on a predetermined axis in each of the plurality of rectangular areas; A variance calculating means for obtaining a variance of a distribution of gray-scale luminance values obtained by the projecting means; and determining a defect based on the variance value calculated by the variance calculating means for each of the plurality of rectangular regions. Based on the result includes a determination means for determining acceptability of the inspected workpiece.

Therefore, according to the present apparatus, the projection processing,
By the distributed processing, the quality of the image to be inspected can be determined while suppressing the influence of luminance unevenness (illumination unevenness or shading) other than a defect of the inspected work body that occurs in the direction of the predetermined axis.

For this reason, even if the contrast is low, the spatial resolution is not reduced, so that small spots can be easily detected.

Further, since low-contrast unevenness can be automatically detected, there is no variation in the quality judgment standard among operators, as compared with, for example, the case where visual inspection is performed visually, and the quality is stable. Also, the throughput does not depend on the operator. Further, a result is obtained in which no oversight of a defect due to the fatigue of the worker and a change in the determination standard do not occur.

According to a second aspect of the present invention, there is provided a surface inspection apparatus according to the first aspect.
The surface inspection apparatus according to claim 1, further comprising control means for executing the projecting means and the variance calculating means while moving the target area to be divided by the area dividing means by a predetermined amount, wherein the determining means comprises a plurality of variance calculating means By integrating the results, the quality of the work to be inspected is determined.

Therefore, according to the surface inspection apparatus of the second aspect, the inspection can be performed a plurality of times while shifting the position of the rectangular area. In addition, it is possible to determine the acceptability of the work to be inspected by integrating a plurality of inspections.

For this reason, the quality of the work to be inspected can be determined with high accuracy while suppressing the influence of the division position of the rectangular area.

According to a third aspect of the present invention, there is provided a surface inspection apparatus according to the first aspect.
In the surface inspection device according to the above, the predetermined axis is a side extending in the same direction as the luminance unevenness generated in the image to be inspected by illumination, or the unevenness in luminance generated in the image to be inspected by the photographing means, constituting a frame of a rectangular area. is there.

Therefore, according to the surface inspection apparatus of the third aspect, it is possible to obtain the variance value related to the luminance value distribution while suppressing the influence of uneven illumination and shading.

For this reason, it is possible to detect, with high accuracy, unevenness in painting and unevenness in paint, which is a defect of the work body to be inspected, which occurs in a direction perpendicular to the direction of shading and shading.

According to a fourth aspect of the present invention, there is provided a surface inspection method for judging pass / fail of a work to be inspected. A photographing step of photographing, and an image processing step of judging pass / fail of the work to be inspected based on the inspected image acquired in the photographing step,
The image processing step includes an area dividing step of dividing the target area of the inspection image into a plurality of rectangular areas, a projecting step of projecting a pixel value on a predetermined axis in each of the plurality of rectangular areas, A variance calculating step of calculating a variance of a distribution of gray-scale luminance values obtained in the projecting step; and determining a defect based on the variance value calculated by the variance calculating means for each of the plurality of rectangular regions, and determining the determination result. The variance calculation step calculates a variance value based on the grayscale histogram.

Therefore, according to the method, the projection processing,
By the distributed processing, it is possible to suppress the influence of luminance unevenness other than the defect of the inspected work body that occurs in a predetermined direction.

Therefore, it is not necessary to repeatedly acquire data for calibration, and low-contrast luminance unevenness can be detected at high speed and with high accuracy.

According to a fifth aspect of the present invention, there is provided a surface inspection method according to the fourth aspect.
Wherein the projecting step projects the luminance value of each pixel on a predetermined axis extending in the same direction as the luminance unevenness generated in the image to be inspected by the illumination, or the luminance unevenness generated in the image to be inspected by the photographing means. The variance calculating step includes a step of calculating a variance value based on a distribution of gray-scale luminance values obtained by projection.

Therefore, according to the surface inspection method of the fifth aspect, particularly, the influence of illumination unevenness and shading is suppressed, and the luminance value distribution caused by coating unevenness, which is a defect of the main body distributed in a direction perpendicular to this, is suppressed. The variance can be determined.

[0029] For this reason, in particular, it is possible to detect uneven coating with high accuracy. A surface inspection method according to claim 6, wherein the control step includes executing the projection step and the variance calculation step while moving the target area to be divided in the area division step by a predetermined amount. The determination step further includes:
The quality of the work to be inspected is determined by integrating the results of the variance calculation steps performed a plurality of times.

Therefore, according to the surface inspection method of the present invention, it is possible to automatically perform a plurality of inspections while shifting the position of the rectangular area, and integrate the inspections of the plurality of inspections. Can be determined.

Therefore, it is possible to judge the quality of the work to be inspected with high accuracy while suppressing the influence of the division position of the rectangular area.

[0032]

[First Embodiment] An outline of a configuration of a surface inspection apparatus 100 according to a first embodiment of the present invention will be described with reference to FIGS. FIG. 1 is a diagram illustrating an overall configuration of a surface inspection apparatus 100 according to Embodiment 1 of the present invention, and FIG. 2 is a diagram illustrating a configuration of an image processing unit 23 illustrated in FIG.

The surface inspection apparatus 100 includes a central control unit 10
Control unit 20, illumination control unit 21, camera control image input unit 2
2, an image processing unit 23, a camera 30, a lighting device 31, a half mirror 32, and a work mounting unit 33. An OPC photosensitive drum 34 (work to be inspected) is arranged in the work mounting section 33. The photosensitive drum 34 is irradiated with light from above by the illumination device 31 and the half mirror 32. The specularly reflected light reflected from the photosensitive drum 34 is captured by the camera 30 and output to the camera control image input unit 22 as an image signal.

The work mounting section 33 is controlled by the control section 20. Thereby, the mounted photosensitive drum 34
Rotates around a drum rotation axis. The illumination 31 emits light based on the control of the illumination control unit 21. Camera 30
Captures an image of the surface of the photosensitive drum 34 based on the control of the camera control image input unit 22. As the camera 30, a line sensor camera is used as an example.

Each of the control unit 20, the illumination control unit 21, the camera control image input unit 22, and the image processing unit 23 is comprehensively controlled by the central control unit 10. Thereby, the photosensitive drum 34 mounted on the work mounting section 33
Illumination and imaging are performed in synchronization with the rotation of. The output of the camera 30 is converted into two-dimensional information in the camera control image input unit 22 and output to the image processing unit 23 as an image signal.

The image processing unit 23 includes a rectangular area dividing unit 40,
It includes a projection unit 44, a variance calculation unit 46, a pass / fail judgment unit 48, a display unit 50, a rectangular area division data holding unit 52, a characteristic reference value holding unit 54, and a memory 56.

The rectangular area dividing section 40 extracts the inspected area from the inspected image, and further divides the inspected area into a plurality of rectangular areas. The projection unit 44 projects a pixel value in a predetermined direction for each rectangular area. The variance calculation unit 46 calculates the variance of the gray-scale luminance values for each rectangular area using the projection result. The pass / fail judgment unit 48 judges pass / fail of each rectangular area based on the variance value, and further judges pass / fail of the work 34 to be inspected. The pass / fail judgment result is displayed on the display unit 50. In addition, the display unit 50 can visually display not only the pass / fail judgment but also the entire processing in the image processing unit 23. Note that these processes are managed by the central control unit 10 as described above.

Here, the operation of the image processing section 23 will be described with reference to FIG. 3 which is a flowchart. FIG. 3 is a flowchart for explaining the operation of the image processing unit 23. First, an image signal is received from the camera control image input unit 22 (step S1). Then, the rectangular area division data is acquired from the database (rectangular area division data holding unit 52) constructed in advance. Here, the rectangular area division data includes information on the inspection area, the rectangular size, and the division start initial value A in the inspection area.

Based on the rectangular area division data, a division start position for dividing the inspection area is determined (step S).
3). Subsequently, based on the rectangular area division data, the inspection area is divided based on the division start position (Step S
4). Thereby, a plurality of rectangular areas are extracted.

FIGS. 4 and 5 are diagrams for explaining the operation of the rectangular area dividing section 40. FIG. In the image to be inspected shown in FIG. 4, a shading phenomenon occurs in the regions D1 and D2 except for the central region D0, and a luminance unevenness due to uneven illumination occurs in the region D3. In addition, in the area D4, uneven brightness due to uneven coating occurs.

The rectangular area dividing section 40 determines a region to be inspected from an image to be inspected based on information on the region to be inspected, and further determines a division start position based on information on a division start initial value A. Note that the division start initial value A may be “0”. In FIG. 4, a pixel (X1, Y3), a pixel (X2, Y3), and a pixel (X1,
A region surrounded by four points Y2) and pixels (X2, Y2) is extracted as a region to be inspected. If the division start initial value A is A0, the pixel (X1, Y1) and the pixel (X
2, Y1) becomes a reference position for extracting a rectangular area (Y1 = Y3-A0).

Subsequently, the rectangular area dividing section 40 performs rectangular division based on information on the rectangular size. In the case shown in FIG. 5, the pixel (X1, Y1), the pixel (X2, Y1),
An area determined by the four points of the pixel (X1, Y2) and the pixel (X2, Y2) is divided into a total of 12 rectangular areas.

Subsequently, referring to FIG. 3, after the image to be inspected is divided into a plurality of rectangular areas, the quality of each rectangular area is determined (step S5). After the pass / fail determination for each rectangular area is completed, it is determined whether the work 34 to be inspected is a non-defective product or a defective product (step S6).

FIG. 6 is a flowchart for explaining the pass / fail judgment processing for each rectangular area. Referring to FIG. 6, first, projection unit 44 performs projection processing on the Y axis for each rectangular area (step S11). More specifically, for each rectangular area, the luminance values of the pixels arranged in the X-axis direction are integrated, that is, projected onto one side of the rectangular area (hereinafter, referred to as projection on the Y-axis). Then, this value is divided by the number of pixels constituting the rectangular area. As a result, one-dimensional shading luminance information in the Y-axis direction is obtained for each rectangular area. Subsequently, the variance calculating unit 46 calculates a variance value based on the one-dimensional gray-scale luminance information after the projection process for each rectangular area (step S12).

Then, the pass / fail judgment unit 48 judges pass / fail based on the variance value for each rectangular area in accordance with the characteristic reference value read from the database (characteristic reference value holding unit 54) constructed in advance (step S13). . The pass / fail judgment result for each rectangular area is stored in the memory 56 (step S14).

FIG. 7 is a flowchart for explaining the quality judgment processing of the work 34 to be inspected. The non-defective product determination unit 48 determines the quality of the work 34 to be inspected based on the result of the quality determination for each rectangular area stored in the memory 56 (step S15). If it is determined that the product is non-defective, a message indicating that the product is non-defective is displayed on the display unit 50 (Step S).
16) If it is determined that the work 34 to be inspected is defective, the display unit 50 displays that it is defective (step S17).

Next, a specific example of the processing from the projection processing to the pass / fail judgment will be described with reference to FIGS.
Here, each rectangular area shown in FIGS. 4 and 5 is represented by a symbol shown in FIG. 8 (P (1, 1) to P (1, 3), P
(2,1) to P (2,3), P (3,1) to P (3,
3), P (4,1) to P (4,3)).

FIG. 9 is a diagram for specifically explaining the processing contents from the projection processing to the quality judgment.
FIG. 4 is a diagram for specifically explaining a quality determination result of a rectangular area. The graphs and images shown in FIGS. 9 and 10 can be visually displayed using the display unit 50. Note that the arrangement of the graphs in FIGS. 9A and 9B corresponds to the arrangement of the rectangular areas in FIG.

As described above, the projection unit 44 projects (integrates) the luminance value of each pixel constituting the rectangular area on the Y axis. As a result, as shown in FIG. 9A, a distribution of gray-scale luminance values corresponding to each Y coordinate is obtained. Further, FIG.
A grayscale histogram is created based on the one-dimensional grayscale luminance distribution shown in FIG. FIG. 9B shows a grayscale histogram corresponding to the grayscale luminance distribution in FIG. 9A.

Subsequently, the variance calculating section 46 calculates the variance of the density histogram shown in FIG. 9B. The pass / fail determination unit 48 receives the result and classifies the variance into three levels according to the characteristic reference value (large variance, medium variance, and small variance). FIG. 9C shows the result of classifying the variance values. For example, rectangular areas P (1,2), P (2,2), P (3,
In 2), the regions P (1,1) to P (4,
1) and P (1,3) to P (4,3) have larger variance values. Further, based on the variance classification, FIG.
Rectangular areas P (1,2), P surrounded by thick solid lines shown in FIG.
It is determined that (2,2) and P (3,2) are defective.

The result of the pass / fail judgment in each rectangular area is sequentially stored in the memory 56 as described above. And
This is used for determining whether the inspection target work 34 is a good product or a defective product. As a method of judging the quality of the work 34 to be inspected, for example, a method of judging the work 34 to be inspected in which at least one rectangular area judged to be defective is defective is cited.

Next, the role of the projection process in the present invention will be described with reference to FIGS. FIG. 11 and FIG. 12 are diagrams for explaining the effect when the projection processing is not performed. FIG. 11A shows a case in which the image shown in FIG. 4 and FIG. As shown in FIG. 11A, the rectangular area P (2,
The grayscale histogram G21 corresponding to 1) has a shape having two peaks under the influence of uneven illumination. In addition, due to the influence of shading, the variation of the grayscale luminance value increases, and the width of the grayscale histogram is widened as a whole.

Therefore, when the variance based on the grayscale histogram shown in FIG. 11A is obtained, the result shown in FIG. 11B is obtained. In FIG. 11B, the rectangular areas P (2,1), P (2,
2), the variance values of P (2, 3) are large. Similarly, in FIG. 11B, the rectangular regions P (1,1), P (3,1), P (4,4) are affected by shading.
1), P (1,3), P (3,3) and P (4,3)
Will increase.

Therefore, based on the variance value shown in FIG. 11B, the rectangular area surrounded by the dotted line (or the dotted line and the thick solid line) shown in FIG. 12 is determined to be defective. That is, a portion where there is no defect such as uneven coating is determined to be defective (a pseudo defect occurs).

On the other hand, when the projection process is performed (FIGS. 9 to 10), the influence of uneven brightness due to shading and uneven lighting is removed, so that it is possible to make an accurate pass / fail judgment.

As described above, when obtaining the variance in each rectangular area, by performing projection processing in a predetermined direction, it is possible to sufficiently remove the influence of shading and illumination unevenness. In particular, the coating unevenness of the OPC photosensitive drum is
As a feature of the manufacturing method, it extends in the X-axis direction on the inspection image. For this reason, by performing the projection process on the Y axis, it is possible to particularly emphasize uneven brightness due to uneven coating. Therefore, it is possible to detect low-contrast shading and brightness unevenness with high sensitivity.

[Embodiment 2] An improved example of the surface inspection apparatus and the surface inspection method will be described. FIG. 13 is a diagram for explaining the configuration of the image processing unit 60 according to Embodiment 2 of the present invention. In the second embodiment, the image processing unit 23
Instead, the image processing unit 60 is used. Image processing unit 60
However, the difference from the image processing unit 23 is that a pass / fail determination unit 62 is included instead of the pass / fail determination unit 48. Pass / fail judgment unit 6
2 integrates the pass / fail determination results of the rectangular area over a plurality of times to determine pass / fail of the work 34 to be inspected.

FIG. 14 is a flowchart for describing the surface inspection processing according to the second embodiment of the present invention. Referring to FIG. 14, image processing unit 23 captures an image to be inspected (step S21). Then, the rectangular area division data (information on the area to be inspected, the rectangle size, and the division start initial value A) is read from the rectangular area division data holding unit 52 (step S22).

Then, a division start position is determined (step S23). The method of determination is the same as in step S3. In the second embodiment, the pass / fail determination process is performed a plurality of times while changing the division start position.

Subsequently, the image to be inspected is divided into a plurality of rectangular areas (step S24). The processing in step S24 is the same as step S4 in the first embodiment. The pass / fail judgment unit 62 judges pass / fail of each of the rectangular regions (step S25). Step S25
Is the same as step S5 in the first embodiment.

Subsequently, the non-defective result of the rectangular area is stored in the memory 56 (step S26). Extract a new rectangular area (division) from a different division start position
It is determined whether or not this is the case (step S27).

If a new division is to be performed, the process proceeds to step S23. In step S23, a new division start position is determined using a different division start initial value A. Then, the processing of steps S24, S25 and S26 is performed (step S27). That is, the variance value is calculated while shifting the position of the rectangular area by a predetermined value, and the variance value at each position is stored in the memory 56.

When the division is completed, the pass / fail judgment unit 62 judges pass / fail of the work 34 to be inspected based on pass / fail judgment of each rectangular area a plurality of times (step S28).

FIG. 15 is a flowchart for explaining the quality judgment processing of the work 34 to be inspected. The non-defective item determination unit 62 integrates the results of the plural non-defective determinations for each rectangular area held in the memory 56, and determines the non-defectiveness of the work 34 to be inspected (step S29). If it is determined that the workpiece is non-defective, the display unit 50 displays that it is non-defective (step S30). If it is determined that the work 34 to be inspected is defective, the display unit 50 indicates that it is defective. A message to the effect is displayed (step S31).

Hereinafter, the processing steps shown in FIGS.
This will be specifically described with reference to FIGS. FIGS. 16 and 17 are diagrams for explaining the pass / fail determination processing of a rectangular area according to the second embodiment of the present invention. FIGS. 18 to 19 show the work 3 to be inspected according to the second embodiment of the present invention.
FIG. 14 is a diagram for describing a pass / fail determination process of No. 4;

FIG. 16 shows that the division start initial value A is A1 (≠ A
0). FIG. 17 corresponds to the case where the division start initial value A is A2 (= 0). By shifting the division start position, the rectangular area to be inspected moves. The initial value A0 of the division start in FIGS.
W / 3 (W = size of the rectangular area in the Y direction).

In FIG. 16, the division start position is shifted by 1/3 of the size W of the rectangular area in the Y direction (A1 = W / 3) as compared with FIGS. In the XY coordinate system, the pixel (X
1, Y4), pixel (X2, Y4), pixel (X1, Y5)
And a region surrounded by four points of pixels (X2, Y5) is a division target (Y4 = Y3-A1). As a result, the rectangular areas P (1 ′, 1 ′) to P (1 ′, 3 ′), P (2 ′,
1 ′) to P (2 ′, 3 ′), P (3 ′, 1 ′) to P
(3 ′, 3 ′), P (4 ′, 1 ′) to P (4 ′, 3 ′)
Is extracted.

When the above-described projection processing and variance calculation processing are performed on these, a rectangular area P surrounded by a thick solid line is obtained.
(1 ′, 2 ′), P (2 ′, 2 ′), P (3 ′,
2 ′), P (4 ′, 2 ′), P (1 ′, 3 ′), P
(2 ', 3'), P (3 ', 3'), P (4 ', 3')
Is determined to be defective. The pass / fail judgment result is stored in the memory 56.

In FIG. 17, the division start position is further shifted by 1/3 of the size W in the Y direction of the rectangular area with respect to FIG. 16 (A2 = 0). In the XY coordinate system, the pixel (X1, Y
3), an area surrounded by four points of a pixel (X2, Y3), a pixel (X1, Y6), and a pixel (X2, Y6) is to be divided. Thereby, the rectangular areas P (1 ″, 1 ″) to P
(1 ″, 3 ″), P (2 ″, 1 ″) to P (2 ″,
3 "), P (3", 1 ") to P (3", 3 "), P
(4 ″, 1 ″) to P (4 ″, 3 ″) are extracted.

When the above-described projection processing and variance calculation processing are performed on these, a rectangular area P surrounded by a thick solid line is obtained.
(1 ", 2"), P (2 ", 2"), P (3 ",
2 "), P (4", 2 "), P (1", 3 "), P
(2 ", 3"), P (3 ", 3"), P (4 ", 3")
Is determined to be defective. The pass / fail judgment result is stored in the memory 56.

When the rectangular area shown in FIG. 5 is used, FIG.
As shown in (1), it is not possible to detect that the rectangular area P (4, 2) is defective because the luminance unevenness has spread over the entire area. However, FIGS.
As shown in FIG. 7, it is possible to detect a defect by moving the rectangular area.

Here, for example, FIG. 10, FIG. 16, FIG.
It is assumed that the pass / fail judgment shown in FIG. 7 is performed three times (the result is stored in the memory 56). FIG. 18 is a diagram in which the results of the pass / fail determination of the rectangular area over three times are integrated. In FIG. 18, an area Z1 indicates an area determined to be defective only once in total, an area Z2 indicates an area determined to be defective only twice in total, and an area Z3 is determined to be defective all three times. The area is shown. In the pass / fail judgment section 62, these three
The inspection of the work 34
Is determined. FIG. 19 shows a case where a portion determined to be defective twice or more in the image shown in FIG. 18 is detected. In this case, an area Z4 including an area D4 corresponding to a defect due to uneven coating is detected. Therefore,
When the pass / fail is determined based on the portion determined to be defective two or more times, the work 34 to be inspected is determined to be defective.

When the pass / fail judgment is made so as to suppress the occurrence of the pseudo defect as much as possible, the work 34 to be inspected in which there is a part (area Z3) judged to be defective in all of the pass / fail judgments a plurality of times is a defective product. Is determined.

When the pass / fail judgment is made so as to detect a true defect as much as possible, a work to be inspected in which a part (areas Z1 to Z3) judged to be defective in any of a plurality of pass / fail judgments is present. 34 is determined to be defective.

The embodiments disclosed this time are to be considered in all respects as illustrative and not restrictive. The scope of the present invention is defined by the terms of the claims, rather than the description of the embodiments, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.

[Brief description of the drawings]

FIG. 1 is a surface inspection apparatus 1 according to a first embodiment of the present invention.
It is a figure which shows the whole structure of 00.

FIG. 2 is a diagram for explaining a configuration of an image processing unit 23 shown in FIG.

FIG. 3 is a flowchart for explaining the operation of an image processing unit 23;

FIG. 4 is a diagram for explaining the operation of a rectangular area dividing unit 40;

FIG. 5 is a diagram for explaining the operation of a rectangular area dividing unit 40;

FIG. 6 is a flowchart illustrating a pass / fail determination process for each rectangular area.

FIG. 7 is a flowchart for explaining a pass / fail judgment process of a work 34 to be inspected.

FIG. 8 is a diagram for explaining the definition of a rectangular area.

FIG. 9 is a diagram for specifically explaining processing contents from a projection processing to a pass / fail determination.

FIG. 10 is a diagram for specifically explaining a quality determination result of a rectangular area;

FIG. 11 is a diagram for describing an effect when a pass / fail determination process for a rectangular area is performed without performing a projection process.

FIG. 12 is a diagram for describing an effect when a pass / fail determination process for a rectangular area is performed without performing a projection process.

FIG. 13 is an image processing unit 6 according to the second embodiment of the present invention.
FIG. 2 is a diagram for explaining a configuration of a zero.

FIG. 14 is a flowchart illustrating a surface inspection process according to the second embodiment of the present invention.

FIG. 15 is a flowchart for explaining a pass / fail determination process for a work 34 to be inspected.

FIG. 16 is a diagram for describing pass / fail determination processing of a rectangular area according to the second embodiment of the present invention.

FIG. 17 is a diagram for describing pass / fail determination processing of a rectangular area according to the second embodiment of the present invention.

FIG. 18 is a diagram for describing pass / fail determination processing of a work to be inspected according to the second embodiment of the present invention.

FIG. 19 is a diagram for describing pass / fail determination processing of a work 34 to be inspected according to the second embodiment of the present invention.

FIG. 20 is a diagram for describing a surface inspection unit for a photosensitive drum.

21 is a diagram for describing uneven brightness when uneven coating occurs on the photosensitive drum illustrated in FIG. 20;

FIG. 22 is a diagram illustrating a change in gray-scale luminance value on line AA ′ in FIG. 21;

[Explanation of symbols]

 Reference Signs List 10 Central control unit 20 Control unit 21 Lighting control unit 22 Camera control image input unit 23, 60 Image processing unit 30 Camera 31 Lighting 32 Half mirror 33 Work mounting unit 34 Work to be inspected 40 Rectangular area division unit 44 Projection unit 46 Dispersion calculation unit 48, 62 pass / fail judgment unit 50 display unit 52 rectangular area division data holding unit 54 characteristic reference value holding unit 56 memory 100 surface inspection device

 ──────────────────────────────────────────────────続 き Continued on the front page F-term (reference) 2F065 AA49 AA61 BB08 BB16 BB17 BB24 DD03 DD05 FF04 GG01 HH13 JJ02 JJ03 JJ16 JJ25 JJ26 LL37 QQ08 QQ23 QQ24 QQ25 QQ36 QQ41 QQ43 SS02 SS03 SS04 ACE01AB01 AB03 EA09 EA14 EA20 EB01 EB02 EC02 EC03 ED07 FA10 2H068 AA21 EA41

Claims (6)

[Claims] 1. A surface inspection apparatus for determining the quality of a work to be inspected, means for illuminating the work to be inspected while changing the posture of the work to be inspected, and photographing the surface of the work to be inspected. And an image processing unit that determines the acceptability of the work to be inspected based on the inspection image acquired by the imaging unit, wherein the image processing unit includes a plurality of target areas of the inspection image. Area dividing means for dividing into rectangular areas; projecting means for projecting a luminance value of each pixel on a predetermined axis in each of the plurality of rectangular areas; and projecting means for each of the plurality of rectangular areas. Variance calculating means for calculating the variance of the obtained distribution of gray-scale brightness values; and determining a defect based on the variance value calculated by the variance calculating means for each of the plurality of rectangular regions. The judgment based on the result the includes a determination means for determining acceptability of the inspected workpiece surface inspecting apparatus. 2. The apparatus according to claim 1, further comprising control means for executing the projecting means and the variance calculating means while moving the target area to be divided by the area dividing means by a predetermined amount. The surface inspection apparatus according to claim 1, wherein the quality of the work to be inspected is determined by integrating the results of the calculation means. 3. The predetermined axis, which forms a frame of the rectangular area, extends in the same direction as the luminance unevenness generated in the image to be inspected by the illumination, or the luminance unevenness generated in the image to be inspected by the photographing means. The surface inspection apparatus according to claim 1, which is one side. 4. A surface inspection method for judging pass / fail of a work to be inspected, wherein a photographing step of illuminating the work to be inspected while changing a posture of the work to be inspected, and photographing the surface of the work to be inspected. And an image processing step of determining the quality of the work to be inspected based on the image to be inspected acquired in the photographing step, wherein the image processing step comprises converting a predetermined area of the image to be inspected into a plurality of rectangular areas. A step of dividing a rectangular area to be divided; a step of projecting a luminance value of each pixel on a predetermined axis in each of the plurality of rectangular areas; and a step of projecting each of the plurality of rectangular areas. A variance calculating step of obtaining a variance of a distribution of gray-scale luminance values; and a variance calculating step for each of the plurality of rectangular regions. Determining a defect based on the variance value,
A surface inspection method, comprising: a determination step of determining acceptability of the work to be inspected based on the determination result. 5. The method according to claim 1, wherein the projecting step comprises: a luminance value of each of the pixels on the predetermined axis extending in the same direction as the luminance unevenness generated in the image to be inspected by the illumination, or the luminance unevenness generated in the image to be inspected by the photographing means. 5. The surface inspection method according to claim 4, further comprising: projecting the variance value, wherein the variance calculating step calculates the variance value based on a distribution of grayscale luminance values obtained by the projection. 6. The method according to claim 1, further comprising a control step of executing the projection step and the variance calculating step while moving the target area to be divided in the area dividing step by a predetermined amount. The surface inspection method according to claim 4, wherein the quality of the work to be inspected is determined by integrating the results of the calculation steps.