JPH1010053A - Inspection device for surface defect - Google Patents

Abstract

PROBLEM TO BE SOLVED: To detect even a gentle irregular defect by calculating a defect candidate position on the basis of the space of the brightness pattern boundary area of an image data, and comparing and judging the defect candidate position continuously obtained in time series with a prescribed condition. SOLUTION: An image pickup means 102 takes the image of a brightness pattern, and converts it into an image data of electric signal. An image processing means 103 extracts the boundary area of the brightness pattern from the image data, and performs a calculation as the area where the space of the adjacent boundary areas is not uniform, if present, as a defect candidate position. A defect detecting means 104 executes a prescribed processing by the means 103 every optional time while moving a surface 100 to be inspected or either one of the means 102 and a lighting means 101. When the change of the defect candidate position continuously obtained in time series is fitted to the movement of the surface 100 to be inspected under a prescribed condition, or when a conformed moving object is present in the image, this area is judged as defect.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a surface defect inspection apparatus for inspecting a surface defect of an object to be inspected, for example, a painted surface of an automobile body.

[0002]

2. Description of the Related Art A conventional surface defect inspection apparatus is disclosed in, for example, Japanese Patent Application Laid-Open No. 2-73139. This is because a predetermined light and dark fringe (stripe) pattern is projected on the surface to be inspected, and when there is a defect such as unevenness on the surface to be inspected, a received light image having a difference in brightness (luminance) or a change in brightness (luminance) due to the defect. Is used to detect a defect on the surface to be inspected.

[0003]

However, such a conventional surface defect inspection apparatus has the following problems. For example, in the painting of an automobile body, what is usually called a surface defect is a projection on the painted surface resulting from the application of dust and the like, for example, having a diameter of about 0.5 to 2 mm and a thickness of about 0.5 to 2 mm. Is about several tens of μm. Since the height (thickness) of the projections of this degree is relatively large although the diameter is small, the irregular reflection angle of light becomes large and is easily noticeable. However, a defect called a deco heco has a very large diameter with respect to its thickness, and thus has a small light diffuse reflection angle and is difficult to find. Such deco-health defects are
There is a problem that detection cannot be performed even by using image processing such as differentiation as in the related art.

The present invention has been made in view of such conventional problems, and has as its object to provide a surface defect inspection apparatus which can detect even a rugged irregular defect on a surface to be inspected. Aim.

[0005]

In order to achieve the above object, the present invention irradiates a surface to be inspected with light, creates a light-receiving image based on light reflected from the surface to be inspected, and generates a light-receiving image based on the light-receiving image. In a surface defect inspection apparatus for detecting a defect on a surface to be inspected, an illuminating means for forming a predetermined light and dark pattern on the surface of the object to be inspected, and a received light image obtained by imaging the surface to be inspected as image data of electric signals Image processing means for extracting a boundary region between the light pattern and the dark pattern in the image data, and calculating a defect candidate position based on an interval between the light and dark pattern boundary regions; and Alternatively, a predetermined process is executed by the image processing means at any time while moving either the imaging means or the illumination means, and the defect candidate position obtained continuously in time series is determined by the movement. It determines whether to match the conditions,
And a defect detecting means for determining the defect candidate as a defect if they match.

[0006]

Embodiments of the present invention will be described below in detail with reference to the drawings. FIG. 1 is an explanatory diagram showing a first embodiment of the present invention, and corresponds to claim 1.

In FIG. 1, reference numeral 100 denotes a surface to be inspected.
For example, a painted surface of an automobile body. Reference numeral 101 denotes illumination means for projecting a predetermined light and dark pattern on the surface to be inspected. Reference numeral 102 denotes imaging means for imaging the surface to be inspected and converting the light / dark pattern into image data of an electric signal;
For example, it is a video camera such as a CCD camera. Also, 1
An image processing unit 03 extracts a boundary region between the bright pattern and the dark pattern in the image data, and calculates a defect candidate position based on an interval between the adjacent bright and dark pattern boundary regions. Reference numeral 104 denotes a defect candidate obtained by executing predetermined processing by the image processing means at an arbitrary time while moving any one of the inspection surface or the imaging means and the illuminating means, and continuously obtaining the defect candidates in time series. It is a defect detecting means for judging whether or not the position matches the above-mentioned movement under a predetermined condition, and if so, judges the defect candidate as a defect.
The image processing unit 103 and the defect detection unit 104 are configured by, for example, a computer.

According to the above arrangement, a predetermined light / dark pattern is projected on the surface to be inspected by the illuminating means, and the light / dark pattern is converted into electric signal image data by capturing the image with the imaging means. Next, the image enhancing means extracts a boundary region of the light and dark pattern from the image data, and if there is a region where the interval between the adjacent boundary regions in the image is not uniform, there is a high possibility that there is a deco-health defect there. Therefore, the position is calculated as a defect candidate position. next,
In the defect detecting means, a predetermined process is executed by the image processing means at an arbitrary time while moving any one of the inspection surface or the imaging means and the illumination means. Here, if the change in the defect candidate position obtained continuously in time series matches the movement of the inspection surface or the illumination and the camera under predetermined conditions, the defect candidate can be determined as a defect. That is, if there is a moving object (region) that matches the above movement in the image, the region is determined as a defect.

FIG. 2 to FIG. 4 are views showing a second embodiment of the present invention. In FIG. 2, reference numeral 1 denotes an illumination device for projecting a predetermined light-dark pattern on the surface 6 to be inspected. Reference numeral 2 denotes an imaging unit for imaging the surface to be inspected and converting the light / dark pattern into image data of an electric signal, for example, a video camera such as a CCD camera. Reference numeral 3 denotes an image processing device that processes image data obtained by the camera 2. Reference numeral 4 denotes a defect detection means for detecting a defect 7 from the time-series continuous image data processed by the image processing apparatus 3, and is a computer such as a personal computer.

In this embodiment, it is assumed that the camera 2 and the illuminating device 1 are fixed, and the surface 6 to be inspected is moving in a direction indicated by an arrow in FIG. 2 by means of a conveyor (not shown).

Next, an example of a procedure for extracting a defect candidate area in the image processing apparatus 3 will be described. As shown in FIG. 2, when the light-dark pattern is irradiated on the surface 6 to be inspected by the illumination device 1 and the reflected light is captured by the monochrome camera 2, a gray-scale image as shown in FIG. 3 (original image) is obtained. Here, if the deco-healing defect is near the boundary between the light and dark patterns, the boundary line of that part becomes an image distorted along the unevenness of the deco-healing defect.

In FIG. 3, first, the image processing apparatus 3 inputs an original image (step 1: S1). Here, the horizontal direction of the image is x, and the vertical direction is y. In the next step, an edge detection process such as differentiation is performed on the original image to extract a region having a luminance change (S2). When the obtained differential image is binarized with a threshold value of a predetermined luminance level, a binary image is obtained in which the area where the luminance changes is white and the other areas are black (S3). Subsequently, labeling (labeling: S4) and area / centroid coordinate calculation (S5) are performed on the white region of the image. Next, an isolated point removal process is performed to obtain an image of only the light and dark pattern boundary region necessary for the detection of the deco-healing defect (S6). This can be realized by, for example, a process of removing a region having a smaller area than the light-dark pattern boundary region.

Next, the interval between the light and dark pattern boundary areas is calculated (S7). This can be calculated from the run list in the x direction of the image (S6), that is, the start point and end point coordinates of the white area in one line. If there is no deco-healing defect 7 on the surface 6 to be inspected, the interval between the adjacent light and dark pattern boundary regions is substantially constant. When the deco-healing defect 7 is present, the light-dark pattern boundary region is distorted, and the interval between the light-dark pattern boundary regions in that portion is largely changed. Therefore, since there is a high possibility that the deco-healing defect 7 exists at the position where the change has occurred, the coordinates are set as defect candidate positions (S8).

Next, an example of a defect detection procedure in the computer 4 will be described. The computer 4 reads the defect candidate position up to the previous time from the memory (S9), and calculates the movement amount d1 from the current defect candidate position calculated in S8 (S10).

In this embodiment, a description will be given assuming that the surface 6 to be inspected moves in the x direction of the image as indicated by the arrow in FIG. 3 (no movement in the y direction). Therefore, the movement amount d1 of the defect from the previous image to the current image is x of the current defect candidate.
It can be calculated as the difference between the direction coordinates and the x-direction coordinates of the previous defect candidate.

Next, the movement amount d2 of the inspection surface 6 is calculated (S11). In the present embodiment, since the inspection surface 6 moves on the transport conveyor, for example, the rotation amount of the conveyor drive source is detected by a pulse generator or the like, and the movement amount d2 can be calculated from the detection result. It is determined whether or not there is a defect based on the degree of coincidence of the movement amounts d1 and d2 thus obtained (S12). For example, if the difference between d1 and d2 is smaller than a predetermined value dref, the defect candidate moves in the same manner as the surface to be inspected 6, so it is determined that the probability of the defect is high, and the number of matches of the defect candidate is determined. The variable m is incremented by one (S13). Such a series of processing is performed on the image data that is continuous in time series, and when the variable m becomes a predetermined value or more, the defect candidate is determined to be a defect and stored (S14). That is, the defect 7 moves as shown in FIG. 4 with a change in time, and if this movement coincides with the movement of the inspection surface 6 itself, it is determined that the defect 7 is a real defect. Note that the processing procedure, determination method, and the like in the image processing unit and the defect detection unit are not limited to the present embodiment.

Next, a third embodiment will be described. This embodiment is an embodiment corresponding to claim 2. As shown in FIG. 5, the larger the angle θ of the irregularities of the defective portion, the greater the distortion of the light-dark pattern boundary line. Therefore, in order to detect a smaller defect, the interval between the light and dark patterns may be narrowed. However, if the distance is too narrow, the influence of irregularities due to “yuzu skin” which does not become a defect increases. Further, since the present invention is based on a detection principle utilizing distortion of a light-dark pattern boundary line due to a defect and movement of a surface to be inspected or a camera and a lighting device, the number of the boundary lines reflected per screen is preferably two or more. . Therefore, as described above, the light and dark pattern is set in consideration of the angle θ, the influence of the yuzu skin, and the number of boundaries per screen.

For example, a sample of the minimum size of a deco healing defect to be detected is prepared, the three-dimensional shape of the defect is measured, the angle θ is obtained, and the defect of the minimum size can be detected. The pitch of the light and dark patterns and the ratio of the light and dark pattern widths at which the line distortion can be captured in the image received by the camera may be calculated from the angle θ or determined experimentally.

Next, a third embodiment will be described. This third embodiment is an embodiment corresponding to claim 3. According to the present invention, when there is an area that does not need to be inspected such as a processed part on the surface 6 to be inspected, that is, a non-inspection area, the area is detected and the defect detection processing is not performed on the non-inspection area. Things. As shown in FIG. 6, since the light is hardly reflected in the non-inspection area 5 such as a hole, the brightness value is lower than the surrounding surface, that is, the area is dark. Therefore, it is possible to separate the surface to be inspected from the hole at a predetermined threshold value and extract the non-inspection region 5 as shown in FIG. If the defect detection processing is not performed on the non-inspection area 5, even if the light-dark pattern boundary line is distorted by the non-inspection area 5, the processing is performed by masking the non-inspection area 5, so that only the defect is detected. be able to. In addition,
The method for extracting the non-inspection area is not limited to the present embodiment.

[0020]

As described above, according to the present invention, there is obtained an effect that a gently uneven deco-healing defect can be accurately detected regardless of the state of the surface to be inspected.

[Brief description of the drawings]

FIG. 1 is a functional block diagram of the present invention.

FIG. 2 is a diagram showing a first embodiment of the present invention.

FIG. 3 is a diagram showing an image and a processing flow for explaining a defect detection procedure.

FIG. 4 is an explanatory diagram of time-series processing (moving image processing).

FIG. 5 is a diagram showing a relationship between an angle θ and a distortion of a light-dark pattern boundary line.

FIG. 6 is an explanatory diagram of extraction of a non-inspection area.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Illumination device 2 CCD camera 3 Image processing device 4 Computer 5 Non-inspection area 6 Inspection surface 7 Defect 100 Inspection surface 101 Illumination means 102 Imaging means 103 Image processing means 104 Defect detection means

Claims (3)

[Claims] 1. A surface defect inspection apparatus that irradiates a surface to be inspected with light, creates a light reception image based on light reflected from the surface to be inspected, and detects a defect on the surface to be inspected based on the light reception image. An illumination unit for forming a predetermined light and dark pattern on the surface of the object to be inspected; an imaging unit for converting a received image obtained by imaging the surface to be inspected into image data of an electric signal; and the light pattern in the image data. Image processing means for extracting a boundary area between the light and dark pattern and calculating a defect candidate position based on the interval between the light and dark pattern boundary areas; and moving one of the inspection surface or the imaging means and the illumination means. A predetermined process is executed by the image processing means at an arbitrary time, and it is determined whether or not the defect candidate positions continuously obtained in time series match the movement under the predetermined condition. Surface defect inspection apparatus characterized by comprising mule and determining defect detecting means the defect candidate as a defect, a. 2. The surface defect inspection apparatus according to claim 1, wherein a light-dark pattern interval of the illumination means is set based on an angle due to unevenness of the defect. 3. The image processing apparatus according to claim 1, wherein the image processing unit detects a non-inspection area from the image data, and calculates a defect candidate position from the detected image data other than the non-inspection area. Surface defect inspection equipment.