JP3177945B2 - Surface defect inspection equipment - Google Patents

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 suitable for inspecting a surface defect of an object to be inspected, for example, a surface defect of a painted surface of an automobile body.

[0002]

A conventional surface defect inspection apparatus of this type is disclosed, for example, in Japanese Patent Application Laid-Open No. Hei 6-213,642.
However, such a conventional surface defect inspection apparatus inspects a paint surface defect on a surface to be inspected, and displays the result as a display defect mark M ₁ , M ₂ , M _3.
In the case where the defect is displayed as, a defect adjacent portion where a plurality of defects are closely mixed in a predetermined range on the inspection surface is detected, and the defect having the highest degree of defect among the defects in the defect adjacent portion is represented by the representative display defect mark. (For example,
This is displayed as a display defect mark M ₁ ).

However, in such a conventional surface defect inspection apparatus, the defect having the highest degree of defect among the defects near the defect is displayed as a representative display defect mark. Since there was a problem that it took time to perform processing related to display and the entire inspection time became longer, it was an issue to solve such a problem.

The present invention has been made to solve such a conventional problem. By simultaneously processing a plurality of defects as one defect at an average position, the defect detection processing is performed. It is an object of the present invention to provide a surface defect inspection apparatus capable of shortening a processing time and an inspection time.

[0005]

According to a first aspect of the present invention, there is provided a surface defect inspection apparatus for irradiating a surface of an object to be inspected with light and reflecting light from the surface to be inspected. In a surface defect inspection apparatus that creates a light-receiving image based on the light-receiving image and detects a defect on the surface to be inspected based on the light-receiving image, an illumination unit that forms a predetermined light and dark pattern on the surface to be inspected, Means for converting a received light image obtained as a result into electric signal image data, and extracting only a component having a high frequency component and a level equal to or higher than a predetermined value among spatial frequency components in the image data as a defect candidate, and Image processing means for calculating the area and barycentric coordinates of the candidate area; and performing predetermined processing by the image processing means at any time while moving either the inspected surface or the illumination means and the imaging means. It is determined whether or not the defect candidate area obtained by continuously executing in a row matches the inspection surface or the movement of the illuminating means and the imaging means under a predetermined condition. A defect detection means for judging the defect candidate area as a defect, and an average position of the plurality of defect candidate areas when the defect detection means judges a plurality of defect candidate areas as defects simultaneously at an arbitrary time and within a predetermined range. Calculating the plurality of defects as one defect at the average position, and displaying the plurality of defects as one defect when displaying a defect occurrence position based on the defect detection result. It is characterized in that the display mark indicating the judgment and the display mark indicating another defect are provided with different display means.

In the embodiment of the surface defect inspection apparatus according to the present invention, as described in claim 2, the display means determines the size of the defect based on the result of the defect detection, and determines the size of the defect. The display mark may be determined accordingly.

[0007]

As described above, according to the first aspect of the present invention, a predetermined light / dark pattern is projected on the surface to be inspected by the illuminating means, and the light / dark pattern is imaged by the image pickup means to convert the light / dark pattern into an electric signal image. Convert to data.

Next, the image processing means extracts only a high frequency component and a component whose level is equal to or higher than a predetermined value among the spatial frequency components in the image data of the light and dark pattern. Here, the high-frequency component in the image data is a portion having a luminance change such as an uneven defect, and by extracting only the component whose level is equal to or more than a predetermined value as described above, a candidate considered to be a defect is obtained. Is extracted as a defect candidate area. And in the image processing means,
The area and barycentric coordinates of the defect candidate area are calculated and obtained.

Next, in the defect detecting means, one of the inspected surface or the illuminating means and the imaging means is moved, that is, the other is fixed, so that the defect on the inspected surface can be detected in the processed image. It moves in synchronization with the above movement. Therefore, if a defect candidate is synchronized with the movement in the image, it is determined to be a defect.

Here, when the defect detecting means judges that a plurality of defect candidate areas are defective at the same time and within a predetermined range at the same time, the judging means determines an average position of the plurality of defects. Since the plurality of defects are calculated and determined as one defect at the above average position, the amount of data handled in the post-processing is reduced, and the processing can be sped up.

As described above, in order to inspect the entire surface to be inspected in the first aspect of the present invention, the object to be inspected or the illuminating means and the imaging means are sequentially moved so that the field of view of the imaging means covers the entire surface to be inspected. It is configured to scan.

Next, in the defect detecting means, when a plurality of defects are determined as one defect, and the defect occurrence position is displayed, the display mark is different from the display mark of another defect detected alone. Since different display means are provided, the post-processing worker judges, based on the display result, whether a plurality of defects are present in a solid state or whether they are occurring alone by using a display mark. It will be.

[0013]

According to the surface defect inspection apparatus according to the first aspect of the present invention, since the above-described configuration is employed, a plurality of defects are regarded as one defect at an average position simultaneously with the defect detection processing. Since the defect is determined by performing the processing, the amount of data handled in the post-processing can be reduced, and a remarkably excellent effect that the processing time and the inspection time can be reduced is brought about. .

In the case where a plurality of defects are determined as one defect and the defect occurrence position is displayed, the display mark is different from the display mark of the other defect detected alone. This provides a remarkably excellent effect that it is possible for a worker in a post-process to easily determine whether a plurality of defects exist as a group or a single defect based on the different display results. It is.

[0015]

DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of a surface defect inspection apparatus according to the present invention will be described with reference to FIG.

In FIG. 1, reference numeral 1 denotes an object to be inspected, for example, an automobile, whose painted surface is an inspected surface 1a. Reference numeral 2 denotes illumination means for forming a predetermined light and dark pattern on the inspection surface 1a of the inspection object 1. Reference numeral 3 denotes an imaging unit for converting a light-receiving image obtained by imaging the surface 1a to be inspected, that is, the light / dark pattern into image data of an electric signal, for example, a video camera such as a CCD (solid-state image sensor) camera.

Reference numeral 4 denotes only a component having a high frequency component and a level equal to or higher than a predetermined value among spatial frequency components in the image data obtained by the image pickup means 3 is extracted as a defect candidate, and the area of the defect candidate area is extracted. (For example, the number of pixels) and image processing means for calculating barycentric coordinates.

Reference numeral 5 designates a predetermined process performed by the image processing means 4 at any time while moving either the object 1 (inspection surface 1a) or the illuminating means 2 and the image pickup means 3. The defect candidate area which is continuously executed in a time series and is obtained in a continuous image processed in the time series is moved by the inspection object 1 (the inspection surface 1).
a) It is a defect detection means which determines whether or not the movement of the illumination means 2 and the imaging means 3 matches under a predetermined condition, and if the movement matches the predetermined number of times or more, determines the defect candidate area as a defect.

Further, 6 calculates an average position of the plurality of defects when the plurality of defect candidate areas are determined to be defective at the same time and within a predetermined range by the defect detection means 5 at the same time. This is a determining means for determining the plurality of defects as one defect at the above average position.

The image processing means 4, the defect detecting means 5, and the judging means 6 are constituted by a computer 7, for example.

The above configuration corresponds to, for example, an embodiment described later with reference to FIGS.

Further, when the defect occurrence position is displayed based on the defect detection result determined by the defect detection means 5, a display mark indicating that a plurality of defects have been determined as one defect, and a display mark indicating that other defects have been determined as one defect. The display device may be provided with display means different from the display mark to be displayed.

The above configuration corresponds to, for example, an embodiment described later with reference to FIGS.

[0024]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of a surface defect inspection apparatus according to the present invention will be described below with reference to the drawings.

FIGS. 2 to 7 show an embodiment of the present invention.

In this embodiment, a case will be described in which a painted surface of an automobile body is used as a surface to be inspected.

In FIG. 2, reference numeral 1 denotes an automobile body to be inspected, and 2 denotes a painted surface of the body 1, that is, an inspected surface 1a.
In this embodiment, the illumination means 2 is assumed to project a bright and dark stripe (striped) pattern in the cross-sectional direction of the body 1.

Reference numeral 3 denotes an image pickup means for picking up an image of the surface 1a 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 3a denotes a camera holder capable of freely adjusting the angle of the camera 3, which fixes the camera 3 at a predetermined position and angle. This camera holder 3a is fixed to a camera stand 3b. Here, the size of the camera visual field in the moving direction of the inspection target surface 1a is represented by W
And

Reference numeral 4 denotes image processing means for processing the image data obtained by the camera 3, and reference numeral 5 denotes defect detection means for detecting a defect from the time-series continuous images processed by the image processing means 4. Numeral 6 is a judging means for judging a plurality of defects detected by the defect detecting means 5 as one defect at an average position. These image processing means 4, defect detecting means 5, and judging means 6 are a computer 7 such as a personal computer. It consists of.

In this embodiment, the camera 3 and the illumination means 2
Is fixed, and the body 1 is moving at a speed v in the direction of arrow A in FIG. 2 with a transport conveyor or the like (not shown).

FIG. 3 is a schematic view of the body 1 as viewed from the front. The lighting means 2 and the cameras 3 (hood cameras H1 to H8, roof camera R1) surround the body 1.
To R7, left side cameras SL1 to SL5, right side cameras SR1 to SR5). In FIG. 3, the line toward the body 1 is the field of view of the camera 3, and the adjacent fields of view form a strip-shaped field of view so that the surface of the body 1 is imaged without a gap. Accordingly, the body 1 moves inside the fixed illumination means 2 and the gate-shaped interior of the camera 3 so that the field of view of the camera 3 can scan the entire surface of the body 1 (the surface 1a to be inspected).

In this embodiment, as shown in FIG.
The body 1 resting on 6 is moved along a rail 17 by a conveyor 18
And passes through the inside of the illuminating means 2 and the camera 3 in the form of a gate.

Next, an example of a procedure for extracting a defect candidate area in the image processing means 4 will be described with reference to FIGS. 4A, 4B and 5C and FIG. 5 (Image processing means 4: S1 to S7). .

As shown in FIG. 4, when the inspection surface 1a on which the stripe pattern is projected is picked up by the monochrome camera 3, a gray-scale image as shown in FIG. 4A (S1: original image) is obtained. Can be This step corresponds to step S1 shown in FIG.
Is equivalent to

At this time, the inspection surface 1 in the field of view of the camera 3
If there is an uneven defect E on a, light is diffusely reflected at the defect E, and thus the defect appears in the image as a region having a brightness (luminance) different from that of the surroundings. For example, when there is a defect E in the bright stripe as in the original image S1 shown in FIG. 4A, the image is displayed as a dark area.

Step S in FIG. 5 is performed on the original image S1.
In step S3 of FIG. 5, edge detection processing such as differentiation is performed, and in step S3 of FIG. 5, binarization is performed using a threshold value of a predetermined luminance level. As shown in FIG. A binary image is obtained, which is white and black otherwise.

Next, labeling (labeling) is performed on the white area of the image in step S4 in FIG.
In step S5, the coordinates of the area and the center of gravity are calculated. Here, in the binary image, utilizing the characteristics that the defect E is a small isolated point and the boundary of the stripe pattern is a large area vertically traversing the screen, the step E of FIG.
When the area determination processing for removing a region larger than the predetermined area value from the binary image in 6 is performed, an area determination image S6 in which only isolated points having a small area remain as shown in FIG. 4C is obtained.

Since the extracted area having a small area is highly likely to be a genuine defect, the area (the number of pixels of the area) and the coordinates of the center of gravity are determined in step S7 of FIG. Store as a defect candidate list.

Next, an example of the procedure of defect detection and defect determination in the defect detection means 5 and the determination means 6 will be described with reference to FIG. 5 (defect detection means 5 and defect determination means 6: S8 to S15) and FIGS. This will be described with reference to FIG.

FIGS. 6A to 6F are examples of area determination result images processed continuously in a time series from a certain time T to T + 5t. When these images are superimposed, FIG.
It will be something like shown below.

In this embodiment, the x-axis is taken in the horizontal direction of the image, and the y-axis is taken in the vertical direction.
It is assumed that the image moves from right to left in the x-axis direction as shown in (f), and the width (number of pixels) of the image in this moving direction is L. Thus, for example, in the images at time T and T + t, if the defect E moves right beside and there is no change in the coordinate in the y direction, the difference between the coordinates of the center of gravity of the defect E in the x direction is the number of moving pixels d1, and the sign is the moving direction. Represent.

First, in the defect detecting means 5, FIG.
In step S8, as shown in FIG.
The defect candidate list at the time T is read from the image processing means 4, and the movement amount d1 for each defect candidate area is calculated as described above from the data up to the time T (hold list).

Here, the moving pixel number d2 is a moving amount of the body 1 in the image, and is calculated in step S9 based on body moving information such as a conveyor conveying speed, for example.

For example, if the defect E moves the image without changing the coordinates in the y direction, it can be calculated by the following equation (1).

The number of moving pixels d2 = (inter-image time t × moving speed v × image size L) / camera visual field W (1) inter-image time t: time difference between two temporally different images to be compared.

Moving speed v: moving speed of the body 1

Image size L: The number of pixels in the image in the body moving direction. For example, if the body 1 moves in the x direction in an image of x × y = 512 × 480 pixels, L = 512.

Camera field of view W: The size of the camera field of view in the moving direction of the inspection surface. For example, t = 0.1 [s], v =
100 [mm / s], L = 512 [pixels], W = 120
If [mm], then d2 = 42.7 [pixels].

The method of calculating the number of moving pixels d2 is as follows.
It is not limited to this embodiment.

Next, in step S10 of FIG. 5, it is determined whether or not each defect candidate area is a real defect based on the movement amounts d1 and d2. That is, a moving object synchronized with the movement of the body 1 is detected from the two images processed in chronological order. An area that moves the same as the body 1 is a defect, and an area that does not match the movement of the body 1 is a defect. It is determined that there is no (ie, noise).

For example, if the movement amounts d1 and d2 satisfy the following conditional expression (2), the movement almost coincides with the movement of the body 1, so that it can be determined that the possibility of a real defect is even higher.

| D1−d2 | <Δd (2) Δd: The above-described determination processing is repeated for an image obtained in a time series according to a determination value in consideration of an error, and the number of matches for one defect candidate is determined. Is greater than or equal to a predetermined number, the defect candidate is determined to be a defect. For example, as shown in (a) to (f) of FIG. 6, if a defect appears on the screen six times before it passes, the determination value of the number of matches is six or less. The setting of the value may be determined experimentally.

The above-described defect determination procedure is not limited to this embodiment.

If there are a plurality of areas determined to be defective in step S10 of FIG. 5 within a predetermined range, it is determined in step S1 that there are a plurality of closely adjacent defects that exist in close proximity.
Judge at 1. For example, the field of view of one camera is xx
If y = 150 mm × 100 mm,
As shown in FIG. 7, when a plurality of areas are determined to be defects at a certain time at the same time, it is within a range that there is no problem even if they are determined to be a plurality of proximity defects. Here, the range to be determined as the plurality of proximity defects is at a glance without a worker's eyes moving in the post-process,
It is desirable that the distance is within a range (that is, the size) in which all of a plurality of adjacent defects can be recognized, and even if it is strictly determined experimentally based on the relationship between the worker's viewing angle and the degree of defect recognition. Good.

Then, at step S10, a plurality of areas are determined to be defective at the same time, and if it is determined at step S11 that the number is n or more, it is determined to be a plurality of proximity defects.
In step S12, the average coordinates of the x and y coordinates are calculated from the barycenter coordinates of those areas, and in step S13, the average is stored in the defect list as one defect existing at the average coordinates. Here, a predetermined value may be written in the area to indicate that a plurality of defects are stored as one defect.

As described above, by making a plurality of defects one defect at the average coordinate position, the data amount is reduced, and the processing time and data communication time relating to the defect display processing to be described later are shortened. As a result, the time required for the entire inspection can be reduced.

As a result of the above processing, a defect candidate area which is not determined to be a defect but may still be a defect is stored as a hold list in step S14 for processing with the next image data.

Next, in step S15, a determination is made based on the test start / end information from a sensor (not shown).

As described above, the above series of processing is repeatedly performed on the images of all the cameras 3 attached so as to scan the entire surface of the body 1 as shown in FIG. By doing so, defect data on the entire surface of the body 1 is stored. That is, the defect inspection process ends at the same time that the body 1 has passed through the surface defect inspection device of the present embodiment.

The procedure for determining a plurality of proximity defects is not limited to the present embodiment.

Next, an embodiment of the display means will be described with reference to FIGS.
It will be described based on.

The display means (not shown) for displaying the result of the defect detection reads the defect list data for all the cameras 3 in step S16 of FIG. 8, and calculates the actual defect occurrence position from the data in step S17. . For example, as shown in FIG. 9, when printing out a defect position by superimposing it on a body development view, a marking position matching the body development view on printer paper may be calculated. This can be calculated because the relative positional relationship between the camera 3 and the body 1 is known.

Next, the sizes (M ₁ , M ₂ , M ₃ ) of the defects are determined according to the area data of the defects as shown in FIG. 9, and the display mark is determined in step S18. Here, since the area data has a predetermined value in order to distinguish a plurality of proximity defects from other independently generated defects as described above, as shown in FIG. To select.

When the display marks of all the defects are determined, a predetermined display process is executed in step S19.

As in the prior art, the size (size), number, and type of defects are determined, and a defect display mark is set in accordance with the result. Although there was a drawback that the worker of the process was confused and the workability was reduced, in the present invention,
Regardless of the size (size), number, or type of defects, the essence is to inform the post-process worker whether the defects are occurring alone or in close proximity. Therefore, the effect that the workability in the post-process is surely improved can be obtained.

[Brief description of the drawings]

FIG. 1 is a functional block diagram showing an embodiment of a surface defect inspection apparatus according to the present invention.

FIG. 2 is a schematic plan view showing an embodiment of a surface defect inspection apparatus according to the present invention, together with a functional block diagram.

FIG. 3 is an explanatory front view showing an embodiment of a surface defect inspection apparatus according to the present invention.

FIG. 4 is an explanatory diagram showing, in one embodiment of a surface defect inspection apparatus according to the present invention, changes due to processing of an image projected by a camera, divided into (a) to (c).

FIG. 5 is an explanatory diagram showing a defect candidate area extraction procedure (S1 to S7) in the image processing means and a defect detection and defect determination procedure (S8 to S15) in the defect detection means and the determination means.

FIG. 6 is an explanatory diagram showing changes in an area determination result image processed continuously in a time series from a certain time T to T + 5t, separately for (a) to (f).

FIG. 7 is an explanatory diagram showing an image obtained by superimposing the area determination result images shown in FIG. 6;

FIG. 8 shows a defect display procedure on the display means (S16 to S1).
It is explanatory drawing which shows 9).

FIG. 9 is an explanatory diagram showing a situation in which a defect position is displayed on a developed view of a body.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Inspection object (automobile body) 1a Inspection surface 2 Illumination means 3 Imaging means (camera) 4 Image processing means 5 Defect detection means 6 Judgment means 7 Computer

Continuation of the front page (56) References JP-A-8-86634 (JP, A) JP-A-8-94333 (JP, A) JP-A-5-209844 (JP, A) (58) Fields investigated (Int) .Cl. ⁷ , DB name) G01B 11/00-11/30 102 G01N 21/84-21/958

Claims (2)

(57) [Claims] 1. A surface for irradiating a surface to be inspected of an object to be inspected with light, forming a light-receiving image based on reflected light from the surface to be inspected, and detecting a defect on the surface to be inspected based on the light-receiving image. In a defect inspection apparatus, an illumination unit for forming a predetermined light and dark pattern on a surface 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 a spatial frequency component in the image data Image processing means for extracting only a component having a high frequency component and a level equal to or higher than a predetermined value as a defect candidate and calculating the area and barycentric coordinates of the defect candidate area; The defect candidate area obtained by executing predetermined processing successively in time series by the image processing means at any time while moving one of them is obtained, and the defect candidate area obtained therefrom is the surface to be inspected or the illumination device. A defect detection unit that determines whether or not the movement of the step and the imaging unit is matched under a predetermined condition, and determines that the defect candidate area is a defect if the number of matches is equal to or more than a predetermined number of times; When a plurality of defect candidate areas are determined to be defects at the same time and within a predetermined range, an average position of the plurality of defects is calculated, and the plurality of defects are determined to be one of the average positions. Means for displaying a defect occurrence position based on a defect detection result, a display mark indicating that the plurality of defects have been determined as one defect, and a display means different from a display mark indicating another defect. A surface defect inspection device, comprising: 2. The surface defect inspection apparatus according to claim 1, wherein the display means is means for determining a size of the defect based on the result of the defect detection and determining a display mark according to the size. .