JPH04152254A - Surface state inspection device - Google Patents

Abstract

PURPOSE:To have accurate and certain inspection including chromatic unevenness free from projections/recesses by determining the adaptivity factor of the concentration histogram of the photographed image data to the normal distribution of that of many articles of acceptable goods, and using the bottom as a threshold when its frequency distribution is bimodal distribution. CONSTITUTION:A concentration histogram is determined for the image data photographed by a photographing device, and determination of the adaptivity factor is made corresponding to the difference between the concentration histogram at this time and the theoretical frequency conforming to the normal distribution having respective means of standard deviation and the mean of each concentration histogram which has been determined from many individual samples of acceptable goods. This calculative motion to determine the adaptivity factor is made each time image data is fed to obtain number of adaptivity factors, and if its frequency distribution is bimodal distribution, examination is made by using its bottom as a threshold, and if not, examination is made by comparing the mean of the variable distribution with a preset threshold. Thereby the surface state including chromatic unevenness, etc., free from projections/recesses is sensed with a sense near the human senses.

Description

[Detailed Description of the Invention] [Industrial Application Field] The present invention is applicable to a surface condition inspection device that inspects surface conditions such as scratches, dust, roughness, and color unevenness (S-light color tone) existing on the surface. .

[Prior art] Conventionally, H
By irradiating the surface with e-Ne laser light and utilizing the fact that it is scattered in any direction by the presence of scratches, dust, etc.,
Some devices detect abnormalities on the surface by reading the scattered light.

[1 ill to be solved by the invention] However, the above-mentioned prior art has the following problems (1) to (3).

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

An object of the present invention is to use a compact device configuration to reliably inspect the surface condition, including color unevenness without surface irregularities, with high precision.

[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 comprising an output device for outputting a result, and the verification device calculates a density histogram n(k) for image data captured by the imaging device, and calculates a density histogram n(k) from each of a large number of non-defective samples. The theoretical frequency g (k) that follows a normal distribution with the mean value and standard deviation of each density histogram obtained previously, μu and σu, and the current density histogram n
A large number of compatibility coefficients F can be obtained by calculating a compatibility coefficient F corresponding to the difference between If the frequency distribution of the above-mentioned compatibility coefficient is bimodal, use the valley as a threshold to test the surface condition of each inspected object, and if it is not bimodal,
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 T set in advance corresponding to the surface condition to be tested this time. It was designed to do so.

[Action Co. 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, and the device configuration can be made compact.

(2) Since the surface condition is detected based on the concentration distribution state of the surface, it is possible to detect the surface condition, including color unevenness without surface irregularities, with a sense similar to that of humans.

■The average value and standard deviation of each density histogram obtained from each of a large number of non-defective samples μ
Find the fitness coefficient F corresponding to the difference between the theoretical frequency g (k) that follows a normal distribution with u and σu and the current concentration histogram n (k), and if the frequency distribution of the fitness coefficient F is bimodal, then The surface condition of each object to be inspected 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 the average value Fμ is determined according 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.

[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 compatibility coefficient. It is a distribution map of

The surface condition inspection device 1 includes a television camera 10 (imaging device)
, a verification device 20, and an output device 3o, 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, N groups of data are stored 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 testing operation using the testing bag 3!20 is performed as follows.

(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 test object or the sampling density by the television camera 10, it may not be necessary to use all MXN pixels input to the verification device 2o. , among which mXn (n5M, n≦N) pixels (see Figure 2 (A)), or for example, pixels where N is an even number (see Figure 2 (A)).
A part of the MXN pixels may be used as in (see B).

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

■Theoretical frequency g (
A compatibility coefficient F corresponding to the difference between the density histogram n' (k) and the current density histogram n' (k) is calculated using the following equation (2) or (3). However, this compatibility coefficient F is obtained for the concentration value of g (k)≠0, and in equations (2) and (3), ρ
For bit quantization, L=2β-1.

Here, the above-mentioned theoretical frequency g (k) can be obtained by (a) each density histogram n' (
Find the average value μ and standard deviation σ of k) using equations (4) and (5) below, and calculate Σ by −n'(k) (b) The average value μ of each of the average value μ and standard deviation σ
It is obtained according to a normal distribution with u and σu.

(2) The arithmetic operation for obtaining the above-mentioned conformity coefficients F is performed on the image data of each object to be inspected that is input one after another from the television camera 10, thereby obtaining a large number of conformity coefficients F and creating a frequency distribution thereof.

(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 there is no bimodality, 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). There may be something that exists.

In addition, since there are the same number of thresholds T as the types of abnormalities (P), if T1≦T, ≦...≦Tp (7), then T=Ti( i=1.,...,P)...(8
). If various abnormalities are to be detected at the same time, it is sufficient to adopt the smallest T1 among the various Tms corresponding to the various abnormalities to be detected 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 compact.

Further, 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.

■The average value and standard deviation of each density histogram obtained from each of a large number of non-defective samples μ
Find the fitness coefficient F corresponding to the difference between the theoretical frequency g (k) that follows a normal distribution with u and σu and the current concentration histogram n (k), and if the frequency distribution of the fitness coefficient F is bimodal, The surface condition of each object to be inspected 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 the average value Fμ is determined according 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, the surface condition including color unevenness without surface irregularities can be reliably inspected with high precision using a compact device configuration.

[Brief explanation of the drawing]

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 invention, and Fig. 4 is a distribution diagram of the conformity coefficient. be. 10... Imaging device, 20... Verification device, 30... Output device. Patent applicant: Sekisui Chemical Co., Ltd. Representative Hiroshi 1) Kaoru Figure 2 (A) (B) Frequency distribution conformity coefficient

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 of each density histogram obtained from each of a large number of non-defective samples. Calculate the compatibility coefficient F corresponding to the difference between the theoretical frequency g(k) that follows a normal distribution with average values μu and σu of standard deviation and the current concentration histogram n(k), and calculate the compatibility coefficient F. By performing the operation on the image data of each inspected object that is input one after another from the imaging device, a large number of compatibility coefficients F are obtained and a frequency distribution thereof is created, and if the frequency distribution of the compatibility coefficients is bimodal, then , the surface condition of each object to be inspected is tested using the valley as a threshold, and if it is not bimodal, the average value Fμ of the frequency distribution is determined, and the average value Fμ corresponds 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 comparing it with a preset threshold value T.