JP2904983B2 - Work surface inspection method - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a work surface inspection method for detecting a surface defect such as a painted surface of a work and its smoothness.

[0002]

2. Description of the Related Art For example, when inspecting the surface of a surface to be measured, as shown in FIG. 8A, light from a light projecting means 2 attached to a robot arm or the like (not shown) is applied to a work surface 6 via a convex lens 4. The light is radiated and the light is converged on detection means 8 such as a CCD camera. Further, image processing is performed on the captured image 10a (see FIG. 8B) obtained by the detection means 8 to check the coating state of the work surface 6, and to check for adhesion of dust, presence or absence of scratches, and the like. In this case, by inspecting the work surface 6 using the convergent light, the inspection range that can be inspected at one time can be expanded.

However, in the above case, the work surface 6
If the surface is flat, the detection light is favorably guided to the light receiving surface of the detection means 8. However, if the work surface 6 is a curved surface as shown in FIG.
The captured image 10b has a bright portion 12 and a dark portion 14 that cannot be handled as an inspection target (see FIG. 9B). In addition, the boundary between the bright portion 12 and the dark portion 14 has an unclear portion, that is, the bright portion 1 due to the effect of the painting state of the work surface 6.
Black minute points (hereinafter referred to as isolated points) are likely to occur on the two sides. The isolated point cannot be determined as an isolated point caused by adhesion of dust or the like in later image processing, and may be erroneously determined to be a coating defect. Therefore, there is a method of removing the isolated points from the captured image data by performing a so-called expansion / contraction process.

[0004]

However, when the above-described expansion and contraction processing is performed on all the captured image data, there is a disadvantage that the image processing time is lengthened and the total inspection time is increased.

The present invention has been made to solve this kind of problem. By selectively performing the expansion / contraction processing on captured image data, the image processing time can be reduced, and the overall image processing time can be reduced. An object of the present invention is to provide a work surface inspection method capable of shortening the inspection time.

[0006]

In order to achieve the above object, the present invention provides a light projecting means for irradiating detection light toward a surface to be measured, and a reflected light of the detection light from the surface to be measured. A method for inspecting the surface of a workpiece having a curved surface, using a surface inspection apparatus having a detection unit that receives light, and a condensing optical system that converges the reflected light on a light receiving surface of the detection unit, The surface inspection device is sequentially displaced along the work surface, the detection light is received by the detection means, the process of holding image data, the process of binarizing the image data, and the surface to be measured is a plane. It is characterized in that it comprises a step of determining whether or not the measured surface is a plane, and a step of performing expansion and contraction processing on the binary image data when the surface to be measured is not a plane.

[0007]

When performing binary image processing on image data captured by the detecting means, it is determined whether or not the surface to be measured is a flat surface, and expansion and contraction processing is performed only when the surface to be measured is a curved surface. This eliminates the expansion / contraction process when the surface to be measured is a flat surface, and shortens the image processing time.

[0008]

DESCRIPTION OF THE PREFERRED EMBODIMENTS A work surface inspection method according to the present invention will be described.
Preferred embodiments will be described in detail below with reference to the accompanying drawings.

In this embodiment, a description will be given based on an inspection method using a work surface inspection apparatus in an automobile production line.

As shown in FIG. 1, the work surface inspection apparatus 20 is mounted on a robot 22, and a light source 24 is fixed to an arm 26 of the robot 22 and connected to the light source 24 by an optical fiber bundle 28. A focusing optical system 30 composed of a Fresnel lens and the like and a CCD camera 32 serving as a detecting means are fixed to the wrist part 34. The CCD camera 32 is connected to an image processing device 36 that performs image processing and the like on the work surface 35, and the image processing device 36 and the robot controller 38 are connected.

As shown in FIG. 2, the image processing device 36 converts the image data input from the CCD camera 32 into an A /
The signal is converted into a digital signal by the D converter 40 and input to the image density memory 42 as gradation image data. The gradation image data in the image density memory 42 is converted into binary image data by the image processor 44 and input to the binary image memory 46. The gradation image data stored in the image density memory 42 and the binarized image data stored in the binarized image memory 46 are displayed on a monitor TV 50 via a D / A converter 48 as appropriate. The image processor 4
4, a microprocessor 52, a memory 54, and an external input / output I / F 56 are connected via a bus 58. The external input / output I / F 56 includes a robot controller 3
8 is connected, and an external computer 59 for managing processing results is connected.

Next, the operation of the work surface inspection device 20 and the image processing device 36 configured as described above will be schematically described with reference to a flowchart shown in FIG.

First, the image processing device 36 and the robot controller 38 are initialized (step S2). Subsequently, a processing pattern of an image described later is input from the robot controller 38 to the image processing device 36 (Step S).
4). After the above setting is completed, the robot 22 is driven, and the operation of the arm 26 inspects the light source 24 via the optical fiber bundle 28 and the condensing optical system 30 one by one in a predetermined area of the work surface 35. Light is irradiated, reflected light of the inspection light is incident on the CCD camera 32, and image data is input to the image processing device 36 (step S6).

The image data input to the image processing device 36 is converted into gradation image data as a digital signal by an A / D converter 40 and input to an image density memory 42. The image processor 44 sets a binarization level as a reference for binarizing the image into a bright part and a dark part based on the histogram of the gradation image data (step S8).

Hereinafter, predetermined image processing is performed according to the processing pattern input from the robot controller 38 (step S10).

As a first processing pattern, when the work surface 35 to be inspected is a plane and the gradation image data is binarized, it is converted into binarized image data based on the binarization level, It is stored in the binarized image memory 46 (step S12). Then, in the binarized image data, a dark part isolated in a bright part is extracted as an isolated point (step S14). Based on the size of the isolated point, it is determined whether or not it is dust, and is sorted out (step S1).
6) The number and size of dust in one section in the processing pattern are transferred to the computer 59 via the external input / output I / F 56 and stored (step S18). The above process is performed on all the sections set on the work surface 35 (step S20). After the image processing for all the sections is completed, the computer 59 outputs an inspection result (step S22).

As the second and third processing patterns, when the work surface 35 is a curved surface and a window is set for an image captured by the CCD camera 32, a window having a predetermined processing range is selected. Then, the part corresponding to the dark part of the obtained image is deleted from the image processing target (step S24). Alternatively, after binarizing the image, a window is calculated and obtained based on the distribution of the bright parts, and the dark part is deleted from the image processing target as in step S24 (step S26).

As the fourth and fifth processing patterns, when the work surface 35 is a curved surface and an image synthesis is selected, only the bright portion is extracted from the binarized image having a bright portion and a dark portion, and one frame is extracted. Image synthesis is performed n times until image data of the corresponding number is accumulated (step S28, step S3).
0). Alternatively, a window is calculated and obtained in the same manner as in step S26, and an image of only a bright portion obtained using this window is stored in the binarized image memory 46 for one frame so as not to overlap, and image synthesis is performed (step S32). ,
Step S30). Images obtained in this way include:
In order to prevent erroneous detection of dust or the like at the boundary between the bright part and the dark part, expansion / contraction processing such as removal of minute particles is performed (step S34). Subsequently, as in the first processing pattern, dust detection in step S16 and subsequent steps is performed. By performing processing on the image synthesized as described above, after the bright portions of a plurality of images are captured in one image, image processing can be performed collectively, so that the image processing speed is improved.

Next, the main part of the work surface inspection method will be described with reference to FIG.

First, the work surface 35 is scanned by the CCD camera 32.
Is read and input to the image density memory 42 of the image processing device 36 as gradation image data. On the other hand, data indicating whether or not the work surface 35 is flat is input from the robot controller 38 to the image processing device 36.
Whether or not the work surface 35 is flat is determined by, for example,
The determination can be made based on whether or not the curvature of the work surface 35 to be inspected is equal to or larger than the set curvature. The curvature of the work surface 35 may be stored as teaching data.

When the work surface 35 is flat, the gradation image data is binarized by the image processing processor 44 and stored in the binarized image memory 46.

Further, noise of a certain level or less mixed in the binary image data is removed by performing electrical processing.

In the image data thus obtained, isolated points (isolated black portions on the image) are detected, the number of the isolated points is counted, and the area of each isolated point is measured. Then, based on these results, it is determined whether or not each isolated point is a defective paint spot due to dust or the like, and this is output to the monitor TV 50.

On the other hand, when the work surface 35 is a curved surface, the captured image data is binarized in the same manner as in the case of a flat surface, and noise below a certain level is removed by electrical processing. The expansion / contraction processing shown in FIG. 7 is performed.
By performing the noise removal processing prior to the expansion / contraction processing, the time required for the expansion / contraction processing can be reduced.

As shown in FIG. 5, in the image 60a after binarization and noise removal, since the work surface 35 is a curved surface, the captured image is affected by the paint skin, and the light portion 62 and the dark portion 6 are affected.
4 are unclear, and many isolated points 6
6.

First, by subjecting the binarized image data shown in FIG. 5 to contraction processing, as shown in FIG.
An image 60b from which unnecessary isolated points 66 at a certain level or less that are not defective portions are removed. Further, expansion processing is performed on the image 60b. As a result, in the image 60b, as shown in an image 60c shown in FIG. 7, the boundary between the light portion 62 and the dark portion 64 is clarified, and the defective painting portion 68 such as dust shrunk by the shrinking process is expanded. Be clarified.

As described above, in the image subjected to the expansion / contraction processing, isolated points such as defective paint spots 68 are detected in the same manner as in the case where the work surface 35 is flat, and this number is counted. At the same time, the area of each of the isolated points is measured. Further, based on these results, it is determined whether or not each isolated point is a defective paint spot due to dust or the like, and this is output to the monitor TV 50.

According to the work surface inspection method of this embodiment, when the work surface is a curved surface, by performing expansion and contraction processing on the image data, a defective portion can be reliably detected and isolated. A point is not erroneously detected as a defective part. On the other hand, when the work surface is flat, the image processing time can be reduced by omitting the expansion / contraction process.

[0029]

According to the work surface inspection method of the present invention, the following effects can be obtained.

That is, when performing image processing by binarizing the image data taken in by the detecting means, it is determined whether or not the measured surface is a flat surface. When the surface to be measured is a flat surface, the processing time can be reduced by omitting the expansion / contraction process.

When the surface to be measured is a curved surface, the expansion and contraction processing is performed, so that an isolated point is not erroneously detected as a defective coating.

[Brief description of the drawings]

FIG. 1 is a schematic explanatory view of a work surface inspection apparatus in a work surface inspection method according to one embodiment of the present invention.

FIG. 2 is a schematic explanatory view of an image processing apparatus in a work surface inspection method according to one embodiment of the present invention.

FIG. 3 is an overall flowchart of a work surface inspection method according to an embodiment of the present invention.

FIG. 4 is a flowchart of a main part of image processing of the work surface inspection method according to one embodiment of the present invention.

FIG. 5 is an explanatory diagram of expansion / shrinkage processing of the work surface inspection method according to one embodiment of the present invention.

FIG. 6 is an explanatory diagram of expansion / shrinkage processing of a work surface inspection method according to one embodiment of the present invention.

FIG. 7 is an explanatory diagram of expansion / shrinkage processing of the work surface inspection method according to one embodiment of the present invention.

FIG. 8 is an explanatory diagram of a work surface inspection method in a conventional example.

FIG. 9 is an explanatory diagram of a work surface inspection method in a conventional example.

[Explanation of symbols]

 Reference Signs List 20 work surface inspection device 22 robot 32 CCD camera 35 work surface 36 image processing device 38 robot controller 42 image density memory 44 image processor 46 binary image memory

────────────────────────────────────────────────── ─── Continuation of the front page (56) References JP-A-3-10150 (JP, A) JP-A-62-294946 (JP, A) JP-A-3-152407 (JP, A) JP-A 64-64 82180 (JP, A) JP-A-62-235550 (JP, A) JP-A-2-176978 (JP, A) JP-A-5-164703 (JP, A) JP-A-1-134207 (JP, U) (58) Field surveyed (Int. Cl. ⁶ , DB name) G01N 21/84-21/90

Claims (1)

(57) [Claims] 1. A light projecting means for irradiating detection light toward a surface to be measured, a detection means for receiving reflected light of the detection light from the surface to be measured, and a light receiving surface of the detection means for receiving the reflected light. Using a surface inspection device equipped with a focusing optical system that converges
A method for inspecting a surface of a work having a curved surface, wherein the surface inspection device is sequentially displaced along the surface of the work,
Receiving the detection light by the detection means and holding image data; binarizing the image data; determining whether the surface to be measured is a flat surface; Performing a dilation / shrinkage process on the binarized image data if it is not a flat surface;