JP2000249527A - Surface defect detector and its detection method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a surface defect detector capable of reducing cost of the device, simplifying the system constitution and quickly judging good or bad of a body to be tested by shortening the processing time of the whole surface of the body to be tested. SOLUTION: This device X is provided with an illumination 2 casting light on the surface of a body H to be tested, a CCD camera 3 imaging the surface of the body with a high resolution, an A/D converter 4 A/D-converting the image, a memory 51 storing the image after digital conversion, a low resolution processor 52 thinning out the digital conversion image and indicating the image characteristics with low resolution, a high resolution processor 53 without thinning out the digital conversion image and indicating the image characteristics with a high resolution as they are at high, a measuring part 54 individually measuring the characteristic quantity of the individual processed images, and a good or bad judging device 6 for judging good or bad of the surface of the body by individually comparing the measured value of the individual characteristic quantity and preset judgment standard of good or bad.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a surface defect detecting apparatus and a surface defect detecting method for detecting a defect such as a defective appearance occurring on the surface of an object such as a roof tile.

[0002]

2. Description of the Related Art Conventionally, as this kind of surface defect detection apparatus, as disclosed in, for example, Japanese Patent Application Laid-Open No. 2-190707, a surface of an object such as a roof tile is surrounded (obliquely).
Scattered light scattered from the surface is received from the direction perpendicular to the surface, and the surface image is subjected to CC.
2. Description of the Related Art There has been known an image pickup apparatus that picks up an image with a D camera or the like and processes the picked up image to detect a directional defect such as a linear processing flaw by scattered light.

[0003]

By the way, when detecting a defect on the surface of an object, as in the conventional case,
When light is uniformly irradiated from the surroundings, the scattered light is extinguished, making it difficult to detect defects.

Therefore, the inventor of the present application has previously proposed a surface defect detection device capable of detecting such a defect (see Japanese Patent Application No. 10-325248).

This surface defect detection apparatus irradiates light to the surface of a subject from almost right above and beside the surface to perform high-resolution imaging, and converts an image obtained by the imaging from analog data to digital data. The digitally converted image, that is, a high-resolution image with a large number of pixels in which the intervals between pixels are close, is individually processed for each pixel, and defects associated with changes in the brightness of the surface of the subject are detected. And undulating defects can be detected.

[0006] However, the inventor of the present application has come to find that the following problems exist even in the surface defect detection device proposed before, as the research is further repeated.

That is, in detecting a defect, it is necessary to detect not only a large defect but also a minute defect without fail. Specifically, a high-resolution CCD camera or the like is used to enable the detection of minute defects of about 1 mm width on the surface of the subject. .5
It is necessary to perform a process of expressing a feature with a high resolution of about mm. For this reason, in order to express a feature amount with high resolution on a processing screen, it is necessary to clearly process the feature amount by individually processing each pixel having many closely spaced pixels. As a result, it takes a considerable amount of time to process the entire surface of the object, and the quality of the object surface cannot be quickly determined.

On the other hand, in the case of an object such as a roof tile, the location where a minute defect occurs on the surface of the object may be defined in a predetermined range for reasons such as processing. Therefore, a process is performed in which a specified range of the surface of the object is imaged by a high-resolution CCD camera or the like, and the high-resolution image is subjected to a process of expressing the feature amount of the image while maintaining the high resolution. May be imaged by a low-resolution CCD camera, and a process of expressing the feature amount of the low-resolution image with the low resolution may be performed. In this method, a high-resolution processing area and a low-resolution processing area are separated on the surface of the object, and the entire area of the object surface has to be processed for each pixel at a close interval because of high resolution. Is defined only in the high-resolution area, and in the remaining low-resolution area, processing for each pixel having a coarse interval is sufficient. This makes it possible to reduce the processing load on the entire surface of the subject and reduce the time required for processing the entire surface of the subject. However, if two types of CCD cameras are installed in this way, the cost of the apparatus is increased and the system configuration is complicated.

The present invention has been made in view of the above points, and has as its object to reduce the cost of the apparatus, simplify the system configuration, and shorten the processing time of the entire surface of the subject. It is an object of the present invention to provide a surface defect detection device that can quickly determine the quality of a surface of an object.

[0010]

Means for Solving the Problems In order to achieve the above object, a solution taken by the invention according to claim 1 is to irradiate a surface of an object with light from almost directly above the surface as an apparatus for detecting a surface defect. Irradiating means, an imaging means for imaging an image of the surface of the object illuminated by the irradiating means at a high resolution from almost directly above, and an analog / digital converter for converting the image taken by the imaging means from analog data to digital data. Digital conversion means, image storage means for storing an image digitally converted by the analog / digital conversion means, and processing for reducing the number of effective pixels for the image stored in the image storage means, thereby obtaining image feature values A low-resolution expression unit that expresses the image with a low resolution, and a high resolution without changing the number of effective pixels for the image stored in the image storage unit. High-resolution expression means for expressing an image feature amount; feature-amount measurement means for individually measuring feature amounts of individual processed images respectively expressed by the low-resolution expression means and the high-resolution expression means; A quality judgment unit for judging the quality of the surface of the subject by individually comparing the measured values of the individual characteristic amounts measured by the measurement means and a preset quality judgment reference value, respectively. is there.

In the case of the first aspect, after the digital conversion, a process for reducing the number of effective pixels is performed to express the characteristic amount of the image as a low resolution with a small number of effective pixels, so that a low-resolution processed image with a small number of pixels is obtained. , The feature amount of a relatively large defect is clearly expressed.

On the other hand, the number of effective pixels is not changed after digital conversion for an image obtained by imaging the surface of the object with high resolution.
In other words, by expressing the feature amount of the image while maintaining the high resolution which does not decrease, the feature amount of a minute defect is clearly expressed.

Thus, the minute defect and the relatively large defect are clearly expressed as characteristic amounts individually by a single high-resolution imaging means, and the measured values of these characteristic amounts and the pass / fail judgment reference values are determined. Are individually compared to make a pass / fail decision. Therefore, in the case of a relatively large defect, a process of expressing a feature amount for each effective pixel having a small interval due to low resolution may be performed. In other words, the process of expressing the feature amount for each effective pixel having a large interval becomes unnecessary because of the high resolution required for expressing the feature amount with high resolution. Therefore, the time required for processing the entire surface of the subject is significantly reduced, and the quality of the surface of the subject can be quickly determined.

Further, since a minute defect and a relatively large defect are individually expressed as feature amounts by a single image pickup means, two kinds of image pickup means such as CCD cameras are not required. For this reason, it is possible to suppress an increase in the cost of the surface defect detection device and to simplify the system configuration.

Here, the low resolution expression means thins out the number of pixels of the image stored in the image storage means in order of an integer in at least one of the x-axis direction and the y-axis direction. When the processing is performed to reduce the number of effective pixels at equal intervals, the number of effective pixels is uniformly reduced at predetermined intervals in at least one of the x-axis direction and the y-axis direction of the image. Above, the feature amount of a relatively large defect is effectively expressed without bias.

Moreover, by thinning out the number of pixels in order of at least one of the x-axis direction and the y-axis direction by an integer, the amount of processing for each pixel can be divided according to the integer number of thinned pixels. Become. In addition, if the number of pixels is thinned out by integers in both the x-axis direction and the y-axis direction, the processing amount required for expressing the feature amount with high resolution depends on the product of the integer number of thinned pixels. Will be divided. As a result, the time required for processing the entire surface of the subject is significantly reduced, and the quality of the surface of the subject can be determined more quickly.

Further, a line sensor camera for carrying an object to be transported on a line moving in a predetermined direction and capable of imaging the object to be transported in a predetermined direction on the line. Is applied as an imaging unit, the surface of the subject being transported is imaged by the line sensor camera. As a result, it is possible to detect a defect on the surface of the subject during transportation without stopping the line, thereby eliminating time loss and improving the performance of the apparatus.

According to a fourth aspect of the present invention, there is provided a method of detecting a surface defect, wherein an image of the surface of the object is substantially completely irradiated with light from almost directly above the surface of the object. Image at high resolution from above. Next, the captured image is converted from analog data to digital data and stored. Then, after performing processing for reducing the number of effective pixels on the image stored after the digital conversion, the feature amount of the processed image is expressed with a low resolution. After that, the feature amount expressed in the processed image is measured. After a while
The quality of the surface of the subject is determined by comparing the measured value of the characteristic amount with a preset quality determination reference value.

In the case of the fourth aspect, a feature amount of a relatively large defect is expressed at a low resolution in a processed image having a small number of effective pixels, and a measured value of the feature amount is compared with a pass / fail judgment reference value to compare the measured value of the feature amount with a pass / fail judgment reference value. Is determined based on a relatively large defect feature amount. At this time, if the object surface is judged to be rejected, the processing required for expressing the feature value with high resolution is completely unnecessary, and is very advantageous in reducing the time required for processing the entire object surface. Becomes

Here, the processing for reducing the number of effective pixels is performed by sequentially thinning the number of pixels of an image after digital conversion by an integer in at least one of the x-axis direction and the y-axis direction. In this case, it is very excellent in expressing a relatively large defect feature amount on the processing screen. Further, this is very advantageous in reducing the amount of processing required when expressing a feature amount with high resolution and reducing the time required for the processing.

Furthermore, when the quality of the surface of the object is determined to be good, the resolution of the image stored after digital conversion is kept high without changing the number of effective pixels. Represents the feature of the processing screen. Next, the feature amount expressed in the processed image is measured. Thereafter, if the quality of the surface of the subject is determined by comparing the measured value of the measured feature amount with a preset quality determination reference value, a fine defect in the processed image having a large number of effective pixels is determined. The feature amount is expressed in high resolution, and the measured value of the feature amount is compared with a pass / fail judgment reference value to judge the quality of the surface of the object based on the feature amount of a minute defect. Since the quality determination of the object surface based on the feature amount of the minute defect is limited to the case where the quality determination based on the feature amount of the relatively large defect is a good determination,
This is advantageous in reducing the time required for processing the entire surface of the subject.

[0022]

Embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 shows a surface defect detecting apparatus according to an embodiment of the present invention. In FIG. 1, a surface defect detection apparatus X is provided in the middle of a transport path of a conveyor 11 (line) that transports a subject H such as a tile in a production line 1. The surface defect detection apparatus X includes an illumination 2 as an irradiation unit, a CCD camera 3 (line sensor camera) as an imaging unit, and an A / D unit as an analog / digital conversion unit for converting an image from analog data to digital data.
The image processing apparatus includes a / D converter 4, an image processing device 5 for processing an image, and a quality determination device 6 as quality determination means for determining the quality of the image.

The conveyor 11 is provided with a photoelectric sensor 12 on the entrance side (the left side in the figure) of the surface defect detection device X. The photoelectric sensor 12 detects that the subject H has passed,
At this time, a passing signal 12a is output.

The illumination 2 is provided above the conveyor 11, and irradiates the surface of the subject H placed on the conveyor 11 with light 2a from almost directly above the surface. The two lights 2 are provided side by side in the direction in which the conveyor 11 is arranged (in the figure, the left and right direction). Each illumination 2 includes a light source unit 21 that emits each illumination 2.

The CCD camera 3 is provided between the illuminations 2 and 2 above the conveyor 11, and is configured to capture an image of the surface of the subject H illuminated by each of the illuminations 2 from almost directly above. As the CCD camera 3, a high-resolution 1024-bit CCD camera is used so that the surface of the subject H can be resolved at an interval of 0.5 mm per bit.

The A / D converter 4 converts image data taken at high resolution by the CCD camera 3 from analog data to digital data. Then, as shown in FIG. 2, the digitally converted image expresses a relatively large defect feature amount a and a minute defect feature amount b.

As shown in FIG. 1, the image processing device 5 includes a storage unit 51 as an image storage unit for storing an image, a low-resolution processing unit 52 as a low-resolution expression unit for processing the image at a low resolution, A high-resolution processing unit 53 as high-resolution expression means for processing an image at high resolution, and feature amounts a and b (defect feature amounts) of the processed image processed by the low-resolution processing unit 52 and the high-resolution processing unit 53 A measuring unit 54 is provided as a feature amount measuring means for individually measuring each.

The storage unit 51 can store, hold (store), and retrieve digital data (image) converted by the A / D converter 4.

In the low-resolution processing section 52, processing for reducing the number of effective pixels is performed on an area A (appearing on the left side in FIG. 2) where the feature amount a of a relatively large defect in the image extracted from the storage section 51 appears. , Image feature a can be expressed with low resolution. In particular,
A process for reducing the number of effective pixels at equal intervals in both the x-axis direction and the y-axis direction by sequentially thinning out the number of pixels of the image extracted from the storage unit 51 one by one in both the x-axis direction and the y-axis direction. Is applied. In addition, a feature amount a expressed in a low-resolution processed image subjected to a process of reducing the number of effective pixels is individually subjected to neighborhood processing for each effective pixel,
Processing for expressing the outline of the entire feature amount a is performed. This neighborhood processing will be described later in detail.

The high-resolution processing section 53 has a high resolution without changing the number of effective pixels in an area B (appearing on the right side in FIG. 2) in which the feature amount b of a minute defect in the image retrieved from the storage section 51 appears. The feature b of the image can be expressed as it is. Specifically, the storage unit 5
The number of pixels of the image extracted from 1 is directly replaced with the number of effective pixels, and the feature amount b represented in the high-resolution processed image having a large number of effective pixels is subjected to neighborhood processing for each effective pixel, thereby obtaining the entire feature amount b. Processing for expressing the contour is performed.

The measuring section 54 counts the outline of the entire feature amount a expressed in the low-resolution processed image for each pixel, and also counts the outline of the entire feature amount b expressed in the high-resolution processed image. Is counted for each pixel.

The pass / fail judging device 6 individually compares the measured values of the individual characteristic amounts a and b measured by the measuring section 54 with preset pass / fail judgment reference values.
The quality of the surface of the subject H is determined.

Next, an example of a method for detecting a surface defect by the surface defect detection apparatus X will be described with reference to the flowchart of FIG. In this case, it is assumed that the subject H such as a roof tile is transported while being placed at predetermined intervals in the transport direction of the conveyor 11 (rightward in FIG. 1).

First, in step S1, the conveyor 1
When the subject H conveyed on 1 starts passing through the photoelectric sensor 12 and confirms the start of the passage by the photoelectric sensor 12, the passage signal 12a is output from the photoelectric sensor 12 to the light source unit 21 and the illumination 2 is turned on. The light 2a is emitted from almost directly above the surface of the subject H by emitting light.
Is irradiated. At this time, the passage signal 12a is also output from the photoelectric sensor 12 to the CCD camera 3, and the light 2
The surface of the subject H irradiated in a is imaged with high resolution from above. Thereafter, in step S2, when the subject H has passed through the photoelectric sensor 12 and the completion of the passage is confirmed by the photoelectric sensor 12, the passage completion signal (not shown) is sent from the photoelectric sensor 12 to the light source unit 21 and the CCD camera 3, respectively. ) Is output, and the imaging by the CCD camera 3 is terminated, and the illuminations 2 are turned off.

Next, in step S3, the subject H
After the high-resolution image data obtained by imaging the surface of A is converted from analog data to digital data by the A / D converter 4, steps S4 to S8 and steps S11 to S11 are performed.
At 14, processing by the image processing device 5 is performed.

That is, in Step S4, Step S
The digitally converted image (shown in FIG. 2) converted into digital data in step 3 is stored (stored) in the storage unit 51.

In step S5, the digitally converted image stored in step S4 is retrieved from the storage unit 51, and
As shown in FIG. 4, a thinning process for reducing the number of effective pixels is performed on an area A representing a feature amount a of a relatively large defect in the image. In this thinning-out process, while the number of pixels in the x-axis direction of the image (area A) is fixed, the number of pixels in the y-axis direction is thinned out one by one in order to obtain odd-numbered pixels (1, 3 in this case). , 5,..., 1023), and then, while the number of effective pixels in the y-axis direction of the image is fixed, the number of pixels in the x-axis direction is thinned out one by one in order to obtain odd-numbered pixels (in this case, Is 1,3,5 ... 1
023) is effective, and the number of effective pixels is reduced one by one at regular intervals in both the x-axis direction and the y-axis direction.

In step S6, the low resolution processed image (area A) thinned out in step S5 is subjected to neighborhood processing individually for each effective pixel. In this neighborhood processing, as shown in FIG. 5, the product of the value of the corresponding element (illuminance value) of an array of 3 × 3 pixels centered on the effective pixel and the filter value shown in FIG. The filter processing value is obtained from the sum of the nine products.

Specifically, as shown in FIG. 5, in the neighborhood processing centering on the effective pixel (x, y) = (50, 50), (49, 49), (49, 50), (49) , 5
1), (50, 49), (50, 50), (50, 5)
1), (51, 49), (51, 50), (51, 5)
The value of the corresponding element of 1) is filtered by integration with the filter value shown in FIG. 6, and the sum of 9 products = 5 × 0 + 5
× (−1) + 9 × 0 + 5 × (−1) + 8 × 4 + 9 × (−
1) A filter processing value is obtained from + 8 × 0 + 9 × (−1) + 9 × 0 = 4. That is, the effective pixel (x, y) = (5
The value "8" of the element of (0, 50) is replaced with the filter processing value "4".

In step S7, binarization processing is performed based on the filter processing value obtained in step S6, and the outline of the entire feature amount a is clearly expressed as shown in FIG.

In step S8, the outline of the entire feature amount a clearly expressed in step S7 is measured by the measuring unit 54, and the processing for the feature amount a by the image processing apparatus 5 is completed.

Thereafter, in step S9, a pass / fail judgment is made based on the measured value of the characteristic amount a measured in step S8. Specifically, the measured value of the characteristic amount a and the pass / fail judgment device 6
The quality of the feature a on the surface of the subject H is determined by comparing the magnitude of the feature a with the reference value of the quality a set in advance.

If the pass / fail judgment in step S9 is NG, that is, if the measured value of the characteristic quantity a is larger than the pass / fail judgment reference value, an NG signal is output to step S17 in step S10, The NG signal is stored in the determination device 6. This NG signal is output to a host computer (not shown) via the pass / fail determination device 6, and the subsequent control (defect detection) of the first subject H is stopped.

As described above, for a relatively large defect, the quality is determined by comparing the measured value of the characteristic amount a with the quality determination reference value, so that the number of effective pixels is reduced in the x-axis direction and the y-axis direction. Neighboring processing may be performed for each effective pixel in area A, which is reduced one by one at regular intervals in both cases, and it is not necessary to perform neighborhood processing for every finely spaced effective pixel over the entire surface of the subject.
Therefore, the time required to process the low-resolution area A is shortened to a quarter, and the quality of the feature amount a can be quickly determined. In addition, since the measured value of the characteristic amount a of the relatively large defect and the pass / fail judgment reference value are compared with each other and the control is terminated when the result becomes NG, the neighborhood processing necessary for expressing the characteristic amount with high resolution is performed. Is completely unnecessary, which is very advantageous in reducing the time required for processing the entire surface of the subject H. Further, the number of effective pixels is uniformly reduced one by one at predetermined intervals in both the x-axis direction and the y-axis direction of the image, and a relatively large defect feature amount is effectively expressed on the processing screen without bias. be able to.

On the other hand, if the pass / fail judgment in step S9 is OK, that is, if the measured value of the characteristic amount a is smaller than the pass / fail judgment reference value, the process proceeds to step S11.

In step S11, the digitally converted image stored in step S4 is retrieved from the storage unit 51, and the area B representing the feature amount b of the minute defect remains in high resolution without changing the number of effective pixels. Expresses the feature amount b of the image.

Then, in step S12, a high-resolution processed image including the feature amount b of the image expressed in step 11, that is, the area B in which no thinning processing is performed, is individually subjected to neighborhood processing for each effective pixel. About this neighborhood processing,
This is the same as step S6, and calculates the product of the value of the corresponding element (not shown) of the array of 3 × 3 pixels centered on the effective pixel and the filter value shown in FIG. The filter processing value is obtained from the sum of the products of.

In step S13, binarization processing is performed based on the filter processing value obtained in step S12, so that the outline of the entire feature amount b is clearly expressed.

In step S14, the outline of the entire feature amount b clearly expressed in step S13 is measured by the measuring unit 54, and the processing for the feature amount b by the image processing apparatus 5 is completed.

Thereafter, in step S15, a pass / fail judgment is made based on the measured value of the characteristic amount b measured in step S13. In this case, since it is not necessary to perform the neighborhood process for expressing the feature amount b for each effective pixel over the entire surface of the subject H, it is possible to quickly determine the quality of the feature amount b.

If the quality determination in step S15 is NG, that is, if the measured value of the characteristic quantity b is larger than the quality determination reference value, an NG signal is output in step S16, and the quality is determined in step S17. The NG signal is stored in the determination device 6.

On the other hand, if the pass / fail judgment in step S15 is OK, that is, if the measured value of the characteristic amount b is smaller than the pass / fail judgment reference value, the OK signal is stored in the pass / fail judgment device 6 in step S17. Then, the control for the first subject H ends. Thereafter, the same control is repeated for the next subject H. Note that the NG signal in step S16 and the OK signal in step S17 are also output to the host computer via the pass / fail determination device 6, and control (defect detection) for the first subject H is terminated.

Therefore, in the present embodiment, the minute defect and the relatively large defect are clearly expressed as characteristic amounts a and b by the single high-resolution CCD camera 3, respectively. , B, and the pass / fail judgment reference value are individually compared with each other in magnitude, so that the pass / fail judgment can be performed quickly.

Further, since a minute defect and a relatively large defect are individually expressed as the feature amounts a and b by the single CCD camera 3, imaging means such as two types of CCD cameras are not required. Therefore, the surface defect detection device X
Cost increase and the system configuration can be simplified.

Further, since the subject H conveyed on the conveyor 11 is imaged by the CCD camera 3, it is possible to detect a defect on the surface of the subject H during the conveyance without stopping the conveyor 11, resulting in a time loss. To eliminate
The capability of the device X can be improved.

In this embodiment, the thinning process is performed to reduce the number of effective pixels by one at regular intervals in both the x-axis direction and the y-axis direction.
A thinning process for reducing one by one at regular intervals in one of the axial directions may be performed. In addition, a thinning-out process may be performed to reduce the number of effective pixels by two or more at regular intervals in both the x-axis direction and the y-axis direction. Is reduced according to the product of the integer number of thinned pixels, the time required for processing the entire surface of the object is drastically reduced, and the quality of the object surface can be determined more quickly. Can be performed.

Furthermore, in the present embodiment, the subject H transported by the single conveyor 11 has been described, but the subject may be transported by a plurality of conveyors, and the number thereof is not limited. Absent.

In this embodiment, the NG signal or the OK signal is output to the host computer via the pass / fail judgment device 6. However, the NG signal or the OK signal is output from the conveyor on the conveyor path (downstream of the surface defect detection device). A discharge device for discharging the subject may be provided, and a defect command signal may be output from the host computer to the discharge device when the NG signal is output, so that the defective subject may be automatically discharged from the conveyor.

[0060]

As described above, according to the surface defect detecting apparatus of the first aspect of the present invention, a minute defect and a relatively large defect are imaged by a single high-resolution imaging means.
By processing each coarse and small number of effective pixels at low resolution and expressing the characteristics of relatively large defects, the time required to process the entire surface of the object is significantly reduced, and the quality of the object surface can be determined quickly. In addition to this, it is possible to simplify the system configuration while suppressing an increase in the cost of the surface defect detection device by eliminating the need for two types of imaging means.

According to the surface defect detecting device of the second aspect of the present invention, the number of pixels of the image is thinned out by an integer in at least one of the x-axis direction and the y-axis direction in order to reduce the number of effective pixels at equal intervals. By performing the processing, it is possible to effectively express the feature amount of a relatively large defect without bias. In addition, by thinning out the number of pixels in order of integers, the amount of processing at high resolution can be divided according to the integer number of thinned pixels, and the number of pixels is reduced by integers in both the x-axis direction and the y-axis direction. By thinning out in order, the processing amount at high resolution can be divided according to the product of the integer number of thinned pixels, and the quality of the object surface can be determined more quickly.

According to the surface defect detecting apparatus of the third aspect of the present invention, by capturing an image of the object moving on the line by the line sensor camera, it is possible to eliminate the time loss and improve the performance of the apparatus.

According to the surface defect detection method of the fourth aspect of the present invention, the quality of the surface of the object is determined based on the characteristic amount of the relatively large defect. Eliminates the need for processing at the resolution
This is very advantageous in reducing time.

According to the surface defect detecting apparatus of the present invention, the number of pixels is thinned out by an integer in at least one of the x-axis direction and the y-axis direction in order to express a relatively large defect feature amount. This is very advantageous in reducing the processing time at high resolution.

Further, according to the surface defect detecting apparatus of the present invention, if the quality of the surface of the object is good, the high-resolution processing is performed, so that the processing of the entire surface of the object is required. This is advantageous in reducing time.

[Brief description of the drawings]

FIG. 1 is a schematic configuration diagram of a surface defect detection device according to an embodiment of the present invention.

FIG. 2 is a diagram showing an image after A / D conversion.

FIG. 3 is a flowchart illustrating a control flow according to a surface defect detection method.

FIG. 4 is a diagram showing an image subjected to a thinning process.

FIG. 5 is a diagram showing values of elements of 3 × 3 pixels centered on an effective pixel (50, 50).

FIG. 6 is a diagram showing filter values of 3 × 3 pixels.

FIG. 7 is a diagram showing an image after binarization by a filter value.

[Explanation of symbols]

Reference Signs List 11 conveyor (line) 2 illumination (irradiation means) 3 CCD camera (imaging means, line sensor camera) 4 A / D converter (analog / digital conversion means) 51 storage unit (image storage means) 52 low resolution processing unit (low Resolution expression means) 53 High-resolution processing unit (High-resolution expression means) 54 Measurement unit (Feature amount measurement means) 6 Pass / fail judgment device (Pass / fail judgment means) H Subject X Surface defect detection device

Claims (6)

[Claims] An irradiating means for irradiating the surface of the subject with light from almost directly above the imaging means; an imaging means for imaging an image of the surface of the subject illuminated by the irradiating means from almost directly above with high resolution; Analog-to-digital conversion means for converting an image taken by the imaging means from analog data to digital data; image storage means for storing an image digitally converted by the analog-to-digital conversion means; storage in the image storage means A process for reducing the number of effective pixels for the image obtained, low-resolution representation means for expressing the feature amount of the image at a low resolution, without changing the number of effective pixels for the image stored in the image storage means The high-resolution expression means for expressing the feature amount of the image while maintaining the high resolution, and the low-resolution expression means and the high-resolution expression means, respectively. Characteristic amount measuring means for individually measuring the characteristic amounts of the individual processed images, and separately measuring the measured values of the individual characteristic amounts respectively measured by the characteristic amount measuring means and a preset pass / fail judgment reference value. A surface defect detection device comprising: a quality determination unit configured to determine quality of the surface of the subject by comparing the quality. 2. The method according to claim 1, wherein the low-resolution expression unit thins out the number of pixels of the image stored in the image storage unit in an integer direction at least in at least one of the x-axis direction and the y-axis direction so that the number of effective pixels is equal. 2. The surface defect detection device according to claim 1, wherein a process for reducing the number of defects is performed. 3. The apparatus according to claim 1, wherein the subject is mounted on a line moving in a predetermined direction so as to be able to be conveyed, and the imaging means includes a line capable of imaging the subject conveyed in a predetermined direction on the line. The sensor camera according to claim 1 or 2, wherein the sensor camera is applied.
A surface defect detection device according to item 1. 4. An image of the surface of a subject is imaged at a high resolution from almost directly above the surface of the subject while light is irradiated to the surface of the subject from almost directly above the object. After being converted to data and stored, the image stored after digital conversion is subjected to a process of reducing the number of effective pixels, and then the feature amount of the processed image is expressed with a low resolution, and then the feature expressed in the processed image A surface defect detection method, comprising measuring an amount, and then comparing the measured value of the measured characteristic amount with a preset quality determination reference value to determine the quality of the surface of the subject. 5. A process for reducing the number of effective pixels by thinning out the number of pixels of an image after digital conversion in order of an integer in at least one of the x-axis direction and the y-axis direction. Claim 4
3. The method for detecting surface defects according to item 1. 6. When the quality of the surface of the subject is determined to be good, the feature amount of the processing screen is stored in the image stored after digital conversion without changing the number of effective pixels without changing the number of effective pixels. Expressed, then, measure the feature amount expressed in the processed image, and then compare the measured value of the measured feature amount with a preset quality determination reference value to determine the quality of the subject surface. The surface defect detection method according to claim 4 or 5, wherein: