JPH03220443A - Measuring apparatus of glossiness of painted surface - Google Patents

Abstract

PURPOSE:To measure the glossiness correctly whichever color has the painted surface by photographing dark and bright patterns formed by a projecting means on the painted surface and extracting only a predetermined amount of level signals at the larger side generated from a photographing means. CONSTITUTION:An image of the dark and bright patterns formed on a painted surface by a pattern projecting means M1 is photographed as a level signal indicative of the level of the light by a pickup means M2. Only a predetermined amount of level signals at the larger side among the level signals output from the pickup means M2 is extracted by a peak average value calculating means M3. The average of the extracted values is set as a peak average value. Further, the brightness of a light source M1a possessed by the projecting means M1 is detected by a light amount detecting means M4. In general, when a light having the light amount of 11 is incident upon a plane and a light having the light amount 12 is reflected from the plane, if an angle of incidence is constant, the glossiness is proportional to 12/11. Therefore, the glossiness of the painted surface is detected by a glossiness detecting means M5 in accordance with the ratio between the peak average value and brightness of the light source M1a.

Description

Detailed Description of the Invention [Industrial Application Field 1] The present invention relates to a coating surface gloss measuring device for measuring the gloss of a coating surface such as the body of an automobile.

[Prior art] Glossiness of the painted surface is one of the important points in the quality of the painted appearance, and its quantitative evaluation is strongly desired. Therefore, various inventions and proposals have been made to measure the glossiness of painted surfaces, and one such device is the "Method for Measuring the Glossiness of Painted Surfaces" described in JP-A No. 63-274847. There is.

According to this proposal (parallel stripes are mapped onto the painted surface, the painted surface is imaged with an image sensor, the level difference between the peak and bottom of the obtained image signal is calculated, and the level difference of the painted surface is calculated from the level difference. It is designed to determine the degree of gloss.

[Problems to be Solved by the Invention] However, according to the conventional coating surface gloss measurement device, although there is a relationship between the level difference between the peak and bottom of the image signal and the gloss, the bottom value is Because differences in brightness depending on the color of the painted surface appear as they are, large errors occur depending on the color of the painted surface, and as a result, the measurement results are greatly affected by the painted color, making it difficult to accurately measure the gloss level. could not be measured.

The painted surface gloss measuring device of the present invention was developed in view of these problems, and aims to accurately measure the gloss of any paint color.

聚脹Q Configuration [Means for Solving the Problem] In order to achieve the above object, as a means for solving the problem, the present invention adopts the following configuration L, that is, the gloss of the painted surface of the present invention. a bright and dark pattern projecting means M for projecting a predetermined bright and dark pattern onto the painted surface as illustrated in Table 1 of Table 1; An imaging means M2 that captures an image as a light intensity level signal, and receives a level signal captured and output by the imaging means M2, extracts a predetermined amount of larger values, and calculates the average value of the extracted values. A peak average value calculation means M3 that calculates the peak average value; a light amount detection means M4 that detects the brightness of the light source Mla included in the light-dark pattern projection means M1; and a peak average value calculated by the peak average value calculation means M3. The gist thereof is to include a glossiness determination means M5 for determining the glossiness of the painted surface according to the ratio of the brightness of the light source Mla detected by the light amount detection means M4.

[Function] The painted surface gloss measuring device of the present invention includes a light and dark pattern projection means M
2, the light and dark pattern image projected on the painted surface is imaged as a light intensity level signal by the imaging means M3, and from the output level signal, the peak average value calculation means M3
A predetermined amount of the larger value is extracted by , the average value of the extracted values is calculated as the peak average value, and the brightness of the light source Mla of the bright and dark pattern projecting means M1 is calculated by the light column 8 means M4. Then, the glossiness determination means M5 determines the glossiness of the painted surface according to the ratio between the peak average value and the brightness of the light source Mla.

How is it possible to determine the degree of gloss through the above-mentioned functions? In general, if light with an intensity of 11 is incident on a plane, and light with an intensity of 12 is reflected from the plane, then the incident When the angle θ is constant, the glossiness is +2/
It is known that the light amount 11 is proportional to the peak average value calculated by the peak average value calculation means M3, and the light amount 12 is proportional to the light source M1 detected by the light amount detection means M4. Since each corresponds to the brightness of a,
The glossiness of the painted surface can be determined according to the ratio between the peak average value and the brightness of the light source.

[Example] Next, a preferred example of the present invention will be described in detail based on the drawings.

The painted surface glossiness measuring device of this embodiment uses a vehicle moving on a line conveyor as an object to be measured, and inspects the glossiness of the painted surface.

This embodiment (as shown in FIG. 2) includes a recognition sensor 3 that reads the serial number of a car body 2 that is placed on a line conveyor 1 and has undergone painting work, and a recognition sensor 3 that irradiates the car body 2 with parallel stripes as a light and dark pattern. a stripe pattern projection device 4 for projecting a pattern, and an image pickup tube for capturing a virtual image of parallel stripes projected onto the vehicle body 2 via a mirror 5.
(hereinafter referred to as a TV camera) 6; a personal computer (hereinafter also simply referred to as a personal computer) 7 that determines the vehicle type and paint color of the vehicle body 2 according to signals output from the recognition sensor 3; A robot that drives and controls the position of an image processing device 8 that determines the glossiness of the painted surface of the vehicle body 2 based on an image signal (video signal), and a gate-shaped robot 9 to which a striped pattern projection device 4, a TV camera 6, etc. are attached. It consists of a control panel 10, etc.

The recognition sensor 3 is configured to output a signal according to the serial number attached to the vehicle body 2 to the control device 7 based on pattern recognition, and since its configuration is well known, a description thereof will be omitted.

As shown in FIG. 3, the striped pattern projection device 4 is composed of a flat plate 4a having a large number of equally spaced slits and a light emitting light source 4c that emits scattered light through a diffuser plate 4b. The surface of the vehicle body 2 as an object has a parallel striped pattern with a predetermined pitch (in this example, the interval between the upper bright and dark areas is 1.
5rrrn). In addition, the flat plate 4a
A light amount sensor 4d that measures the amount of light from the light emitting source 4C is provided between the light emitting light source 4C and the diffusion plate 4b.

Furthermore, the TV camera 6 captures a virtual image of parallel stripes projected on the painted surface of the vehicle body 2 via a mirror 5 fixed to a mirror holder 5a, and outputs a video signal according to the intensity of brightness and darkness of the striped pattern. It is. The TV camera 6 is provided with a crest 6a so that the amount of input light can be adjusted.

These striped pattern projection device 4, TV camera 6, and mirror holder 5alL are connected to the jib 9 of the portal robot 9 by the frame 9a.
It is fixed at b.

The gate-shaped robot 9 (Y) is driven and controlled by the robot control panel 10 to move the frame 9a back and forth, left and right, and up and down, thereby moving the striped pattern projector 4, TV camera 6, and mirror holder 5a to the desired position relative to the vehicle body 2. The structure of the gate-shaped robot 9 and the robot control panel 10 is not directly related to this embodiment, so a description thereof will be omitted.

A personal computer 7 (as shown in Table 4) is configured as a logical multiplication circuit that is centered around a well-known CPU 7a, ROM 7b, and RAM 7c, and interconnects these with an external input/output circuit 7d via a bus 7e. The external input/output circuit 7d of the personal computer 7 is connected to a CRT display device (not shown) placed at the site of the painting process in which the car body 2 on the conveyor is painted (in addition to the table recognition sensor 3). .

Image processing device 81 table As shown in FIG. 4, similarly, the CPU 8a, ROM 8b, and RAM 8c are centrally connected, and these, the A/D converter 8d, the D/A converter 8e, and the external output circuit 8f are connected to the bus 8g. It is configured as a logical operation circuit connected to each other. The external input/output circuit 8f of the image processing device 8 is connected with a light sensor 4d, a robot control panel 10, a CRT display device 8h, and an external input/output circuit 7d of the personal computer 7.
are connected in both directions for input and output. Also, A/D
A TV camera 6 is connected to the converter 8d so as to input the video signal output from the converter 8d.
The aperture section 6a of the camera 6 is connected.

The operation of this embodiment configured as described above will be explained with reference to the flowcharts shown in FIGS. 5 to 7. Here, the "PC main routine" shown in FIG. 5 is a process executed by the personal computer 7, and the "image processing main routine" shown in FIG. 6 and the "PC main routine" shown in FIG.
The “glossiness determination processing routine” is a process executed by the image processing device 8.

The painted vehicle body 2 is conveyed at a constant speed by a conveyor, and when it reaches a predetermined position, its serial number is read by a recognition sensor 3. The CPU 7a of the personal computer 7 inputs the serial number read by the recognition sensor 3 via the external input/output circuit 7d.
), and then, based on this serial number, a process is performed to search the ROM 7b for information such as 20 car body types and painted color information (
Step] 10).

Once the vehicle type and color information of the vehicle body 2 is obtained, this information is output to the image processing device 8 via the external input/output circuit 7d (step 120).

Thereafter, the process (step 30) waits for an input from the graphic image processing device 8.

On the other hand, when the CPU 8a of the image processing device 8 receives information about the vehicle body 2 from the personal computer 7 (step)
40) Based on this information, a process is performed to output predetermined position data for each vehicle type to the robot control panel 10 (step 150).

As a result, each motor (not shown) of the gate type robot 9 is driven by the robot control panel 10 to move the tag TV camera 6 to a predetermined position for each vehicle type.

When the TV camera 6 is moved to a predetermined position, T
The crest 6a of the V camera 6 is controlled (step 1
60).

Control of this embossed portion 6a is performed as follows.

First, the CPU 8a opens the striped portion 6a by a predetermined opening degree based on the color information of the vehicle body 2 inputted from the personal computer 7, and inputs a virtual image of the parallel stripes on the vehicle body 2 via the mirror 5 as a light intensity level signal. do.

A video signal as a strength level signal of this light (Table A/D
The data is converted into a digital value by a converter 8d, and is stored in a RAM 8c as an image memory.

The CPU 8a compares the maximum value or minimum value of the video signal converted to a digital value with each reference value and converts the video signal into the aperture unit 6a via the D/A converter 8e so that the level of the video signal is within a predetermined range. and adjust its opening.

As a result, the value of the video signal captured by the TV camera 6 and loaded into the RAM 8c is within a predetermined range (0 to 255
) is considered to be the digital value. Such a video signal is shown in FIG.
represents a line.

Note that the negative side signal of this video signal indicates a synchronization signal.

When the aperture control is performed in step]60, a glossiness determination process is performed to determine the glossiness of the painted surface of the vehicle body 2 from the captured video signal (step 170).

This glossiness determination process (step 170) is performed as follows, as shown in the flowchart of FIG.

First, the light amount Q detected by the light amount sensor 4d is stored in the RAM 8.
c (step 171), and then
For example, the striped image captured by the TV camera 6 is
12 into a predetermined area of the RAM 8c (step 72).

Then, from the data of the captured digital image, a ninth
Create a histogram as shown in the figure (step 17
3). Next, in order to obtain the density of the peak portion of the video signal shown in Fig. 8, the upper (larger density side) OO point is extracted from the created histogram.Step 174: The hatching section in Fig. 9 (represents the extracted 100 points), and further calculates the standard deviation value σ and average value a1 for the values of the 100 points (step) 75
). Next, among the 100 extracted points, data with a value greater than or equal to the calculated average value a1 plus the standard deviation value σ is considered to be data representing noise as shown in Figure 8, and those 100 points are Remove from among the points (step 176:
(See Figure 10).

Then, the average value a2 of these values is calculated again for the pigs that were removed in step 176 and remained (step 177). Subsequently, the degree of gloss is determined from the value obtained by dividing the calculated average value a2 by the amount of light Q detected in step 17 (step 178).

Here, it will be explained how the degree of gloss can be determined from the value obtained by dividing the average value a2 by the amount of light Q.

In general, it is known that if light with an amount of 11 is incident on a plane and light with an amount of 12 is reflected from the plane, the glossiness is proportional to +2/+1 when the incident angle θ is constant. There is.

That is, the glossiness can be expressed as J (J=kl .+2/+1 (kl biproportional constant).

Applying to this example, +1 = 2 ・Light amount Q +2: 3 - average value a2 (k2. k3: proportionality constant), and therefore, glossiness J (J = kl ・k3 ・a2 / (k2 ・Q) Second -a2/Q (k: constant of proportionality).This shows that the glossiness is proportional to Jh<a'l/Q.In other words, the glossiness is calculated from the value obtained by dividing the average value a2 by the light amount ○. can be ranked.

Glossiness information of the painted surface determined as described above (outputted from the upper image processing device 8 to the personal computer 7 (Step 80 in FIG. 6). After this, the process proceeds to Step 40)
Return to

When the personal computer 7 receives the glossiness information from the image processing device 8, it divides the glossiness information into several ranks (step 90 in FIG. 5), and then judges the information on the ranks. The information representing the position is fed back to the painting process via the external Ohata force circuit 7d (step 200). After this, the process returns to step 100 again.

The glossiness ranks described above are determined for each part (pointers P] to P]4 of the vehicle body 2, as shown in FIG. 12.

According to the painted surface gloss measuring device of the present embodiment described above in detail, parallel stripes are irradiated onto the painted surface of the vehicle body 2 by the stripe pattern projection device 4, and the painted surface is imaged by the TV camera 6. The peak value of the image data of the striped pattern is extracted, and then the peak value is statistically processed to calculate the peak average value a2, and the light amount Q of the light emitting light source 4C of the striped pattern projection device 4 is measured by the light amount sensor 4d. Then, the glossiness of the painted surface is determined from the value obtained by dividing the peak average value a2 by the light amount O. Therefore, since the bottom value of the striped image pig is not used to calculate the glossiness as in the conventional example, the calculated glossiness is not affected by the paint color, and the glossiness is not affected by the paint color. It is possible to accurately measure the glossiness of a painted surface, even if the color is different.

In addition, since the light Q of the light emitting light source 4C is monitored when calculating the glossiness, even if the light emitting light source 4C deteriorates, the glossiness can be accurately measured without being affected by the deterioration. . Furthermore, the secondary effect is that it is possible to determine when to replace the light emitting source 4C from the amount of light.

Claims (1)

[Scope of Claims] A light and dark pattern projection means for irradiating a predetermined light and dark pattern onto a painted surface, and an image of the light and dark pattern projected on the painted surface by the light and dark pattern projection means as a light intensity level signal. an imaging means; and a peak average value calculation means for receiving a level signal imaged and output by the imaging means, extracting a predetermined amount of larger values, and calculating an average value of the extracted values as a peak average value. , a light amount detection means for detecting the brightness of a light source included in the light-dark pattern projection means; and a ratio between the peak average value calculated by the peak average value calculation means and the brightness of the light source detected by the light amount detection means. A glossiness measuring device for a painted surface, comprising: a glossiness determining means for determining the glossiness of the painted surface according to the glossiness of the painted surface.