JPH0438455A - Apparatus for inspecting surface state - Google Patents

Abstract

PURPOSE:To enhance inspection accuracy by inspecting the surface state of an object to be inspected using the trough of the frequency distribution of pixel data as a theshold value when said frequency distribution is double-humped and comparing the mean value of the frequency distribution with a preset threshold value when the frequency distribution is not double-humped. CONSTITUTION:A television camera 10 transmits a multilevel image sampled in a pixel unit to an inspection apparatus 20 which in turn calculates the adaptation coefficient F corresponding to the difference between a density histogram and theoretical frequency on the basis of the image inputted to an image memory 22. This adaptation coefficient F is obtained with respect to the image data of each object to be inspected to form the frequency distribution thereof and, when the frequency distribution is double-humped, the trough thereof is set to a threshold value to inspect the surface state of each object to be inspected and, when the frequency distribution is not double-humped, the mean value Fmu of the frequency distribution is calculated and compared with a preset threshold value T to inspect the surface state of each object to be inspected.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a surface condition inspection device for detecting surface conditions such as scratches, dust, roughness, and color unevenness (shading of color tone) existing on a surface.

[Prior art] Conventionally, as a surface flaw inspection device, He was applied to the surface of an object to be inspected.
-Ne laser irradiates light and detects the presence of scratches on the surface based on the degree of scattering by the unevenness of the scratches.

[Problems to be Solved by the Invention] However, the above conventional surface flaw inspection apparatus using the light irradiation-scattering method has the following problems (1) to (4).

■The optical system is complicated and the device is large.

■Surface conditions such as color unevenness that are not accompanied by surface irregularities cannot be detected.

■Detection results do not necessarily match the sense perceived by the human eye.

An object of the present invention is to use a compact device configuration to reliably inspect surface conditions, including color irregularities, with a sense similar to that of humans.

[Means for Solving the Problems] The present invention provides an imaging device that images the surface of an object to be inspected, a verification device that verifies the surface state of the object to be inspected based on the imaging result of the imaging device, and a verification device for the verification device. The inspection device is a surface condition inspection device configured to include an output device that outputs a result, and the verification device obtains a density histogram n(K) for image data captured by the imaging device, and calculates the density histogram n (
Find the mean value μ and standard deviation σ based on K), find the theoretical frequency g (K) of each concentration that follows a normal distribution with the above mean value μ and standard deviation σ, and calculate the above concentration histogram n (K) and the above theoretical frequency. A large number of compatibility coefficients F is obtained by calculating the compatibility coefficient F corresponding to the difference between the compatibility coefficient F If the frequency distribution of the above-mentioned compatibility coefficient is bimodal, the surface condition of each inspected object is tested using the trough as a threshold, and if it is not bimodal, its frequency distribution is The surface condition of each object to be inspected is verified by determining the average value Fμ of the frequency distribution and comparing the average value Fμ with a threshold value T set in advance corresponding to the surface condition to be tested this time. This is how it was done.

[Effect] According to the present invention, the following effects (1) to (4) are achieved.

■The surface condition can be detected using a versatile imaging device such as a television camera, making the device configuration compact.

■Since the surface condition is detected based on the surface concentration distribution, it is possible to detect the surface condition, including color unevenness, with a sense similar to that of humans.

■Concentration histogram n (
compatibility coefficient F corresponding to the difference between K) and the theoretical frequency g (K)
If the frequency distribution of the compatibility coefficient F is bimodal, the surface condition of each inspected object is tested using the valley as a threshold, and if it is not bimodal, the average value Fμ of the frequency distribution is determined. By comparing the average value Fμ with a threshold T set in advance corresponding to the surface condition to be tested this time,
It was decided to examine the surface condition of each object to be inspected. Thereby, it is possible to reliably separate whether the object to be inspected is good or bad, and to improve the accuracy of the test.

[Example] Fig. 1 is a block diagram showing an example of the inspection device of the present invention, Fig. 2 is a schematic diagram showing image data, Fig. 3 is a flowchart showing the inspection procedure according to the present invention, and Fig. 4 is a conformance coefficient. FIG. 2 is a schematic diagram showing a bimodal frequency distribution of .

The surface condition inspection device 1 includes a television camera 10 (imaging device)
, a verification device 20 , and an output device 30 , and inspects the surface of an object to be inspected, such as a thermoplastic foam sheet, for abnormalities.

The basic operations of the surface condition inspection device 1 are as follows (1) to (4)
It is.

(1) The surface of the foam sheet is imaged by the television camera 10.

The television camera 10 transfers a multivalued image sampled pixel by pixel to the verification device 20.

(2) The verification device 20 quantizes the image data of the television camera 10 with an A/D converter 21, for example, at 8 bits (256 gradations), creates a digital image of MXN pixels, and inputs this into the image memory 22. do.

(3) Based on the image input to the image memory 22, the testing device 20 uses the CPU 23 to test whether there is any abnormality on the surface.

(4) The output device 30 displays the test results of the test device 20 and generates an alarm if necessary.

Note that as the imaging device (10), a line sensor having M spatial resolution may be used instead of the television camera. In this case, the line sensor and the object to be inspected are moved relative to each other, Store the data of the N side group in the image memory.

The verification device 20 does not necessarily use the image memory 22, and the
The output data of the /D converter 21 may be input directly to the CPU 23.

However, the verification operation by the verification device 20 is as follows.
This is done as follows (see Figure 3).

(2) Obtain a density histogram n(k) for the image data of MXN pixels (k=density value, n: frequency).

When creating this density histogram n(k), depending on the size of the abnormal part predicted in advance in the object to be inspected or the sampling density by the television camera 10, all MXN pixels input to the verification device 20 may not be used. For example, mXn (05M, n≦N) pixels (see Figure 2 (A)), or pixels where N is an even number (Figure 2 (B)).
) may also be used as part of the MXN pixels.

■To make the histogram smooth, each density value is averaged next to each other.
n (K-1)+ 3 n(K) + 2 n(K+
1) + n (k+2) / 9
...Replace with (1).

(2) Based on the averaged density histogram n' (K), find its average value μ and standard deviation σ.

Σ-n' (K) Σn' (K) ...(
3) ■ Calculate the theoretical frequency g (to) of each concentration according to the normal distribution N (μ, σ1″) with the average value μ and standard deviation σ of the concentration histogram n′ (K).

(2) Find the compatibility coefficient F corresponding to the difference between the density histogram n' (N) and the theoretical frequency g (K) using the following equation (4) or (5). However, this compatibility coefficient F is g (K)≠
For the density value of 0, and in equations (4) and (5), if Ω bit quantization is performed, L=212-1.

g (K) ... (4) g (K) ... (5) ■
The calculation operation to find the conformity coefficient F in the above
By performing this on the image data of each object to be inspected that is input one after another from o, a large number of conformity coefficients F are obtained and a frequency distribution thereof is created.

(2) If the frequency distribution of the conformity coefficient F obtained in (2) above is bimodal as shown in FIG. 4, the surface condition of each object to be inspected is tested using the valley as a threshold.

On the other hand, if it is not bimodal, the following processing is further performed.

■Find the average value Fμ of the frequency distribution of the conformity coefficient F obtained in the above ■, compare the average value Fμ with the threshold value T set in advance corresponding to the surface condition to be tested this time, and find that Fμ≦ T: All good products Fμ>T: All defective products... (6) is determined and the result is output.

At this time, there may be one threshold data T depending on the grade classification (normal/abnormal) of the same type of surface condition, but there may be two threshold data T depending on the grade classification (good/fair/poor). It may be something that exists.

Also, since there are the same number of thresholds T as the types of abnormalities (P), if T1≦T2≦...≦Tp (7), then T=T, according to the abnormality detected this time. (i=1....,P)...(8)
If you want to detect various abnormalities at the same time, it is sufficient to use the smallest T among the various T corresponding to the various abnormalities that you want to detect this time.

Next, the operation of the above embodiment will be explained.

- Surface conditions can be detected using a versatile imaging device such as the television camera 10, and the device configuration can be made more compact.

Furthermore, the processing content is simple, the surface condition can be verified in a short time, and the inspection can be completed even on the conveyance line of the object to be inspected.

■Since the surface condition is detected based on the surface concentration distribution, it is possible to detect the surface condition, including color unevenness, with a sense similar to that of humans.

■Density histogram n' for a large number of image data
Find the fitness coefficient F corresponding to the difference between (K) and the theoretical frequency g (K), and if the frequency distribution of the fitness coefficient F is bimodal,
The surface condition of each test variable is tested using the valley as a threshold value, and if it is not bimodal, the average value Fμ of the frequency distribution is determined, and this average value Fμ corresponds to the surface condition to be tested this time. The surface condition of each object to be inspected was tested by comparing it with a threshold value T set in advance. Thereby, it is possible to reliably separate whether the object to be inspected is good or bad, and to improve the accuracy of the test.

[Effects of the Invention] As described above, according to the present invention, surface conditions including color unevenness etc. can be reliably inspected with a sensation similar to that of a human being, using a compact device configuration.

[Brief explanation of drawings]

Fig. 1 is a block diagram showing an example of the inspection device of the present invention, Fig. 2 is a schematic diagram showing image data, Fig. 3 is a flowchart showing the inspection procedure according to the present invention, and Fig. 4 is a bimodal diagram of the matching coefficient. It is a schematic diagram showing frequency distribution. 10... Imaging device, 20... Verification device, 30... Output device. Patent applicant: Sekisui Chemical Co., Ltd. Representative Hiroshi 1) Kaoru

Claims (1)

[Claims] (1) It has an imaging device that images the surface of the object to be inspected, a test device that tests the surface condition of the test object based on the imaging results of the imaging device, and an output device that outputs the test results of the test device. The verification device calculates a density histogram n(K) for the image data captured by the imaging device, and calculates the average value μ and standard deviation σ based on the density histogram n(K). The theoretical frequency g(K
) is calculated, and a fitting coefficient F corresponding to the difference between the density histogram n(K) and the theoretical frequency g(K) is calculated, and the calculation operation for calculating the fitting coefficient F is performed for each image input one after another from the imaging device. By performing this on the image data of the inspection object, a large number of conformity coefficients F are obtained and a frequency distribution thereof is created.If the frequency distribution of the above-mentioned conformity coefficients is bimodal, the valley is used as a threshold value for each inspection object. If the surface condition is not bimodal, the average value Fμ of the frequency distribution is determined, and the average value Fμ is set as a threshold value T that has been set in advance corresponding to the surface condition to be tested this time. A surface condition inspection device that verifies the surface condition of each object to be inspected by comparison.