JPH02287203A - Optical stripe detection - Google Patents

Abstract

PURPOSE:To enable a stripe to be quantitatively detected on-line in a noncontact condition by obtaining a variation (standard deviation) in the brightness of one-dimensional brightness signals by a processing unit and evaluating the presence or absence and the intensity of the stripe on the surface of an object to be inspected from the value of the standard deviation. CONSTITUTION:An object 1 to be inspected moves in a direction shown by an arrow and has stripes on the surface of the object 1 in a line direction. One-dimensional brightness signals produced when a spatial two-dimensional brightness distribution on the surface of the object 1 is compressed in one direction are detected by a one-dimensional brightness signal detector 2. A variation (standard deviation) in the brightness of the one-dimensional brightness signals obtained by the detector 2 is obtained by a processing unit 3 and the presence or absence and the intensity of the stripes on the surface of the object 1 are evaluated.

Description

[Detailed Description of the Invention] [Industrial Application Field] The present invention provides a detection method for detecting stripes on the surface of an object to be inspected in a non-contact manner without bringing a measurement probe into contact with the surface of the object to be inspected. Regarding.

[Conventional technology]

On coating lines and printing lines for thin steel plates, films, printed matter, etc., uneven coating or printing sometimes occurs due to machine vibrations or other influences, and this appears as stripes in the line direction on the product. There are various strengths and weaknesses of the stripes, but in general, most of them are barely discernable with the human eye. However, even subtle unevenness becomes noticeable to the human eye when laminated, creating a problem.

On the other hand, it is difficult to automate the detection and evaluation of minute changes that humans (experts) perform, so currently offline manual (visual) evaluation is the mainstay, and automation is difficult. It is one of the most lagging areas.

(Problem to be solved by the invention) The conventional method has the following problems.

(1) Since it is a visual inspection by an expert, quantitative evaluation is not performed, resulting in individual differences in evaluation results.

(2) The occurrence of stripes is not a temporary phenomenon, but once it occurs, it continues to occur, so the current offline inspection results in a large number of defective products.

The present invention was proposed in view of these circumstances, and
The purpose of the present invention is to provide an optical stripe detection method that can quantitatively detect and evaluate stripes on the surface of an object to be inspected in a non-contact manner on-line.

<Means for Solving the Problems> The optical fringe detection method according to the present invention illuminates the surface of an object to be inspected with an illumination device, senses a two-dimensional image of the brightness and darkness distribution on the surface of the object to be inspected with an image sensor, and detects brightness and darkness. A signal detection device compresses the two-dimensional brightness distribution on the surface of the inspection object in one direction.
The present invention is characterized in that it is detected as a dimensional bright/dark signal, the standard deviation of the variation in brightness of the one-dimensional bright/dark signal is determined by an arithmetic processing device, and the presence or absence and strength of stripes on the surface of the inspection object are evaluated from the value of the standard deviation. .

(Function) The one-dimensional brightness detection device compresses the spatial two-dimensional brightness distribution on the surface of the object to be inspected in one direction, the arithmetic processing device determines the brightness variation (standard deviation) of the one-dimensional brightness signal, and the arithmetic processing is performed. The presence and strength of stripes on the surface of the object to be inspected is evaluated from the standard deviation determined by the device.

〔Example〕

Examples of the present invention are shown in FIGS. 1 to 9.

FIG. 1 shows an embodiment of the present invention. In FIG. 1, the inspection object l is moving in the direction of the arrow shown in FIG. 1, and stripes are formed on its surface in the line direction (stripe direction). There is. Here, as a definition of the directionality of the stripes, when there are stripes as shown in FIG. 2, the X direction is called the line direction (stripe direction) and the y direction is called the width direction (band direction). In FIG. 1, 2 is a one-dimensional brightness signal for obtaining a -dimensional brightness signal obtained by compressing the spatial two-dimensional brightness distribution on the surface of the inspection object 1 in one direction (adding and averaging the degree of brightness and darkness in one direction). It is a detection device. 3 is the -
This is an arithmetic processing device for determining the brightness variation (standard deviation σ) of the one-dimensional brightness signal obtained by the dimensional brightness-darkness signal detection device 2 and evaluating the presence/absence and strength of stripes on the surface of the inspection object 1.

Next, a method of compressing the spatial two-dimensional brightness distribution in one direction to obtain a one-dimensional brightness signal will be explained with reference to FIG.
Inspection object 1 with an area image sensor such as a D camera
When the surface of the object is shaded, the image becomes as shown in FIG. 3(a). In this image, considering the brightness distribution on one scanning line in the line direction, that is, in the striped direction, since the image contains minute noise in -a, if the brightness of the stripes is clear, This is not a problem, but if the brightness of the stripes is subtle, the brightness and darkness of the stripes will be buried in noise, making it difficult to distinguish between the stripes and the noise. The lines in Figure 3 (Figure 3(b) are shown when the brightness distribution of the scanning lines in several striped directions in al are displayed three-dimensionally by shifting them.Here, the lines in Figure 3+8) When the scanning lines in the direction (stripe direction) are compressed in the width direction (band direction) (adding and averaging the degree of brightness and darkness), the noise in each scanning line is canceled out (because noise is random), and the third
Figure (obtains a one-dimensional brightness signal like C1. Figure 3 (C)
In this case, the noise is removed and only the subtle brightness distribution of the stripes is extracted.

In FIG. 3, the change from (al to (bl) is due to the following reason.

Although (a) shows an image of stripes taken with a camera, the stripes are clearly drawn for easy understanding, but in reality, the difference in shading is barely perceptible to the human eye. (
The method of the present invention is most effective when targeting such subtle stripes).

(bl indicates the brightness distribution of several scanning lines in (a).

First, if one scanning line is considered, the result will be as shown in FIG.

When there is only one strip, it is buried in noise and it is not clear whether there are stripes or not. Even if the standard deviation σ is calculated in this state, it is not possible to determine the presence or absence and strength of the stripes; in other words, the values are almost the same (confirmed by experiment).

Next, when several scanning lines above and below this scanning line are collectively displayed, the result is as shown in FIG.

In this case, it will overlap (I don't know.

Therefore, if the brightness of each scanning line is shifted by a certain value up and down and displayed, the result will be as shown in FIG. 8 (3).

If you look at this, you can see that there are some stripes.

This is easy to understand if you imagine a three-dimensional display (Fig. 8 ■).

Next, in FIG. 3, the reason for changing from ('b) to (C) is as follows.

('b) shows the brightness distribution of some scanning lines.

This brightness distribution includes differences in shading due to the stripes, but because the stripes are subtle, they are buried in noise.As mentioned above, if the standard deviation is calculated as is, the influence of noise will be large and evaluation will not be possible. .

Since image noise is generally random noise, the noise is canceled out by averaging. Therefore, several scanning lines are added and averaged.

To be precise, the flow is as shown in Figure 9 (■). Figure 9 (
bl is shown shifted up and down to make it easier to understand, so if the shift is returned to its original state and averaged, it becomes as shown in Figure 9 (■) (C1).

The noise is canceled out, and only the subtle differences in shading of the stripes are extracted. (Confirmation method by experiment) Regarding the question of whether the difference in shading in Figure 3 (C) could be larger, as mentioned above, Figure 3 fa) has clear stripes for easy understanding. In reality, since we are targeting subtle stripes, the difference in shading in Figure 3 (C1) will also be subtle.

If there are no stripes on the surface of the object to be inspected 1, even if the image appears to have no contrast as shown in Fig. 3(a)', each scanning line has a pattern as shown in Fig. 3(b). ′ contains noise. However, by averaging the degree of brightness, it is possible to obtain a one-dimensional brightness signal with no difference in brightness, as shown in FIG. 3(C)'.

Furthermore, even if there are scratches such as dents on the surface of the inspection object l, by averaging the degree of brightness, it is possible to suppress the influence of the scratches as a difference in brightness.

FIGS. 4 and 5 show a method for realizing the above-mentioned -dimensional contrast signal detection device 2 that performs the above-described processing.

There are three methods shown in FIG.

(1) When the line speed of the inspection object l is sufficiently slow, there is a method shown in FIG. 4. In FIG. 4, 1 is an object to be inspected, and 1 is moving in the direction of the arrow in FIG. 4 is a lighting device for illuminating the surface of the inspection object 1; 5 is an area image sensor; 6 is an image processing device; As shown in FIG. 3 for the dimensional image, by averaging the degree of brightness in the width direction (band direction), a one-dimensional brightness signal is generated. This is a timing signal generator for controlling the operation timing of the area image sensor and the image capture timing of the image processing device. If the sensitivity of the area image sensor is sufficiently high with natural light illumination, the illumination device 4 may be omitted. Furthermore, if the inspection object 1 is not moving (if it is stationary), the timing signal generator 7 may be omitted. The one-dimensional brightness signal obtained by the image processing device 6 is output to the arithmetic processing device 3 in FIG.

(2) FIG. 5 shows a method that utilizes movement of the inspection object 1 in the line direction. In FIG. 5, 1,4°7 is the same as in FIG. 4, so a description thereof will be omitted. In FIG. 5, 5' is a line image sensor, which detects the brightness distribution on a certain straight line in the width direction (band direction) of the surface of the object 1 to be inspected. In FIG. 5, 6' is an image processing device for adding and averaging the degree of each brightness and darkness with respect to the linear brightness and darkness distribution in the width direction (band direction) of the surface of the inspection object 1 obtained by the line image sensor. It is.

If the arithmetic average is determined by the image processing device 6' according to the timing signal of the timing signal generator 7 obtained in accordance with the movement of the inspection object 1, the surface of the inspection object 1 similar to (1) can be obtained. A one-dimensional brightness signal can be obtained in the line direction. The -dimensional brightness signal is then output to the arithmetic processing unit 3 in FIG. If the sensitivity of the linear image sensor is sufficiently high with natural light illumination, the illumination device 4 may be omitted.

(3) FIG. 6 also shows a method that utilizes movement of the object to be inspected in the line direction. In FIG. 6, 1 and 7 are the same as in FIG. 4, so their explanation will be omitted. In FIG. 6, reference numeral 4' denotes a monochromatic slit light generator for irradiating monochromatic slit light onto a certain straight line in the width direction (band direction) of the surface of the object 1 to be inspected. 5
# is a photodetector that is sensitive only to the wavelength of the monochromatic light. Since the photodetector 5'' is sensitive only to the monochromatic slit light, the degree of average brightness on the straight line irradiated with the monochromatic slit light (however, the brightness is limited to the light wavelength of the monochromatic slit light) As the photodetector 5'', a general photodetector equipped with a bandpass filter that transmits only the wavelength of the monochromatic slit light is used. 6
'' is a signal processing device that outputs a signal indicating the average degree of brightness on a straight line in the width direction (band direction) of the surface of the inspection object L obtained by the photodetector 5#, based on the timing of the timing signal generator 7. By outputting according to the signal, (1
) A one-dimensional brightness signal in the line direction of the surface of the object to be inspected is created and output to the arithmetic processing device 3 in FIG.

In this method, within the detectable area of the photodetector 5'',
Care must be taken because the presence of light other than the monochromatic slit light to be detected (having the same wavelength as the monochromatic slit light) causes disturbance. If the influence of ambient light is large,
By providing a suitable light shielding plate, etc., it is possible to suppress the influence of ambient light.

The one-dimensional seven brightness signals such as (C1, (C)' in FIG. Then, the signal 1i (i=1...,
The standard deviation σ of n) is given by the following equation.Next, a specific example showing the effect of the method of the present invention is shown in FIG. FIG. 7 shows the results of measuring the surface of the coated steel plate. This steel plate is currently being evaluated by off-line visual inspection.

As can be seen from FIG. 7, the standard deviation σ obtained by the method and apparatus of the present invention increases as the degree of fringe becomes poorer, and this tendency also agrees well with the visual observation results. this is,
If stripes occur, the degree of brightness will vary in the one-dimensional brightness signal, so the standard deviation σ of the variation in brightness will increase; if no stripes occur, the degree of brightness will be almost constant, so
This is because the standard deviation becomes smaller. This is shown in Figure 3 (C
) and (C)′ can be intuitively understood. By determining this standard deviation σ, it is possible to detect and evaluate the stripes on the surface of the inspection object 1 quantitatively and online in a non-contact manner.

〔Effect of the invention〕

Since the present invention is configured as described above, according to the present invention, the spatial two-dimensional brightness distribution on the surface of the object to be inspected is compressed (the degree of brightness and darkness is reduced) in one direction (band direction) using a one-dimensional brightness/darkness signal detection device. The standard deviation σ of the variation in brightness of the one-dimensional brightness signal obtained by the above-mentioned -dimensional brightness signal detection device is determined by the arithmetic processing device, and the presence or absence of stripes on the surface of the object to be inspected is determined based on the σΦ value. By evaluating the strength and weakness, stripes on the surface of the object to be inspected can be detected and evaluated quantitatively and online in a non-contact manner.

[Brief explanation of the drawing]

Fig. 1 is a diagram showing an embodiment of the present invention, Fig. 2 is an explanatory diagram of the directionality of stripes, Fig. 3 is an explanatory diagram of a one-dimensional brightness signal, Fig. 4,
5 and 6 are diagrams showing an embodiment of the one-dimensional bright/dark signal detection device, FIG. 7 is a diagram showing the effects of the present invention, and FIGS. 8 and 9
The figure is a diagram for explaining the phenomenon of FIG. 3. DESCRIPTION OF SYMBOLS 1... Inspection object, 2... One-dimensional bright/dark signal detection device, 3... Arithmetic processing device, 4... Illumination device, 4'...
- Monochromatic slit light generator, 5... Area image sensor, 5'... Line image sensor, 5''... Light detection device, 6.6'... Image processing device, 6''... Signal Processing device, 7... timing signal generator. (a) (b) (b). Figure (c) Figure (a) (b) (a) (b) (a) (b) Figure

Claims (1)

[Claims] The surface of the object to be inspected is illuminated with a lighting device, the image sensor senses a two-dimensional image of the brightness and darkness distribution on the surface of the object to be inspected, and the two-dimensional brightness and darkness distribution of the surface of the object to be inspected is compressed in one direction using a brightness signal detection device. A one-dimensional bright/dark signal is detected, a standard deviation of variations in brightness of the one-dimensional bright/dark signal is determined by an arithmetic processing device, and the presence or absence and strength of stripes on the surface of the inspection object are evaluated from the value of the standard deviation. Optical fringe detection method