JPH07220058A - Method and device for supporting illumination condition setting - Google Patents

Abstract

PURPOSE:To optimize the illumination condition and the image pickup condition by evaluating the illumination condition and the image pickup condition based on image data obtained by actually picking up the image of an object. CONSTITUTION:An image input part 61 includes an A/D converter which converts the analog video signal outputted from a television camera 20 to digital picture data, and this data is given to a picture memory 62. The image input part 61 generates a picture quality histogram, which shows the picture quality with the brightness on the axis of abscissas, in real time based on the inputted analog video signal. A CPU 65 reads a maximum value and a minimum value of the generated picture quality histogram and calculates an evaluation value V of illumination at a set height (h) of an illuminator in accordance with a specific formula and stores the calculation result in a RAM 67. The illuminator is properly moved to another position in the vertical direction and is fixed to repeat generation of the picture quality histogram and calculation of the evaluation value. A message informing whether a larger evaluation value is obtained or not is displayed on a display device 41 to approximate the illuminator to the optimum set height.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing system for imaging an object using an imaging device under illumination by an illuminating device and processing image data obtained by the imaging, and illuminating the object suitable for the purpose. , To determine or set the installation position, installation angle, luminous intensity, etc. of the lighting device to perform imaging suitable for the purpose, and to select or select the camera, lens, and close-up ring that make up the imaging device , Apparatus and method for assisting decision or setting.

[0002]

BACKGROUND ART In order to automate visual inspection of industrial products and the like, automatic inspection devices have become popular, and image processing systems have been introduced into these automatic inspection devices. In order to realize highly accurate inspection with an automatic inspection device, it is necessary to obtain the optimum image suitable for the inspection purpose. In order to obtain the optimum image, it is important to set the optimum lighting conditions and imaging conditions.

Explaining it concretely by taking an example, in a visual inspection device and a positioning device, a recognition object is imaged by a television camera under illumination by an illumination device. The obtained image data is taken into the image processing device and binarized. Based on the binary image data, the characteristic amount such as the area of the target object and the position of the center of gravity is measured, and the quality of the target object is determined and the positioning is performed.

In order to measure the feature quantity with high accuracy, it is necessary to obtain good binary image data, and therefore it is necessary to set the illumination of the observation system to the optimum state. Here, a good binary image means an image in which the edges of the object in the binary image are smoothly continuous and have few isolated noises (small white dots or black dots).

Therefore, when such a binary image is obtained, it is judged that the illumination of the observation system is set to the optimum state. 2 even if some ambient light is added
The fact that the value image does not change is also a requirement for optimal illumination.

The type of illumination device and the illumination method are selected according to the purpose such as inspection. In the past, the guideline for selecting the lighting device and lighting method was not clearly organized, so what kind of lighting device and lighting method to use was selected by trial and error.

Even if the lighting device and the lighting method are appropriately selected, it is not easy to set the lighting device to the optimum installation position and installation angle. Conventionally, the work of adjusting the position and angle of the illumination device has been performed while looking at the image displayed on the monitor.

[0008] However, according to such a conventional method, it takes skill to determine the position and angle of the lighting device,
It was difficult for an inexperienced worker to adjust to the optimum state. Further, there is a problem that the position and the angle of the lighting device are likely to vary depending on the operator, and the lighting device is not always installed at the best position and angle, and the recognition accuracy changes each time the adjustment is performed.

The illumination condition includes not only the position and angle of the illumination device but also its luminous intensity as an important factor.

More practically, it is preferable to judge whether the illumination condition is appropriate by evaluating the obtained image. For example, the optimum illumination condition for the inspection of non-defective products is that the non-defective products can be reliably discriminated from each other, that is, the illumination condition that the discrimination accuracy is high.

It can be said that the optimum illumination condition for measurement is such that the variation in measured values is small, that is, the illumination condition in which the measurement accuracy is high.

However, according to the above-mentioned conventional adjustment method, there is no guarantee that the illumination condition that can reliably distinguish the good product from the defective product and the illumination condition that the variation of the measured value becomes small are always obtained.

Setting appropriate shooting conditions or shooting environment is also an important matter. For example, it is necessary to install a camera at a position convenient for the inspection system configuration and select an optimum lens in order to ensure a visual field suitable for the inspection purpose. It may also be necessary to use a close-up ring to achieve the desired installation distance and field of view. Given the constraints of using existing lenses, it may be necessary to solve the problem of how to properly set the installation distance and the close-up ring in order to achieve the desired field of view.

[0014]

DISCLOSURE OF THE INVENTION The present invention, without requiring skill, determines or sets illumination conditions such as the installation position, installation angle, and luminous intensity of an illuminating device, a lens, a close-up ring, a type of camera, and an imaging including a set distance of the camera. The purpose is to enable automatic or semi-automatic determination or selection of conditions.

The present invention also provides an illumination condition based on image data obtained by actually photographing an object,
The objective is to evaluate and optimize imaging conditions.

More specifically, if it is a non-defective product inspection,
The illumination condition can be set from the viewpoint of how to reliably distinguish a non-defective product from a defective product and how to obtain a measured value with little variation in measurement.

The present invention provides an apparatus and method for evaluating or optimizing an illumination condition based on real image data obtained by actually capturing an image of an object, or supporting the same. Particularly, in the present invention, the position of the lighting device is adjusted.

A lighting condition setting support device according to the present invention comprises:
Illumination device for illuminating an object, support device for supporting the illumination device in a positionally adjustable manner, imaging device for imaging an object under illumination by the illumination device and outputting a video signal representing an image of the object, imaging Image quality histogram generating circuit means for generating an image quality histogram representing the quality of image quality with respect to brightness based on a video signal output from the device, and illumination evaluation based on the image quality histogram generated by the image quality histogram generating circuit means. Evaluation value calculation circuit means for calculating a value, comparison circuit means for comparing the current evaluation value calculated by the evaluation value calculation circuit means with the previous evaluation value before the position change of the lighting device, and the comparison circuit means An output means for outputting the comparison result is provided.

In the first embodiment, the output means is a display device for instructing the position adjustment direction of the illuminating device according to the comparison result by the comparison circuit means.

In a second embodiment, the support device includes a drive device for changing the position of the lighting device. The output means is a display device for instructing the position adjustment direction of the illumination device according to the comparison result by the comparison circuit means. An input device for inputting a command for driving the drive device and a control device for controlling the drive device in response to the command input through the input device are further provided.

In a third embodiment, the support device includes a drive device for changing the position of the lighting device. Further, there is further provided control means for controlling the drive device according to the comparison result by the comparison circuit means and adjusting the position of the illumination device to the optimum position.

A lighting condition setting support method according to the present invention comprises:
An illumination device that illuminates an object, a support device that supports the illumination device in a positionally adjustable manner, and an imaging device that images the object under illumination by the illumination device and outputs a video signal representing an image of the object In the image processing system,
An image quality histogram representing the degree of quality of image quality with respect to brightness is generated based on the video signal output from the image pickup device, and an illumination evaluation value is calculated based on the generated image quality histogram. The evaluation value is compared with the previous evaluation value before the position change of the lighting device, and the comparison result is output.

According to the present invention, since the illumination conditions are optimized so that a good image can be obtained based on the image data obtained by actually capturing the object, no skill is required,
Even if the workers are different, the same good image is always obtained.

In the first embodiment, the operator manually sees the displayed instructions, and in the second embodiment semi-automatically,
The height of the lighting device is adjusted.

In the third embodiment, since the height setting of the lighting device is completely automated, it is easier to set the position of the lighting device, and the efficiency and rationalization of the work can be realized.

The main part of the image quality histogram generation circuit means described above can be used as an edge image generation device.

The present invention provides an edge image generating apparatus using the image quality histogram generating circuit means.

An edge image generating apparatus according to the present invention is an image pickup apparatus for picking up an image of an object and outputting a video signal representing the picked-up image, and an A / D for converting the video signal output from the image pickup apparatus into digital image data. Conversion means, A / D
An image memory for storing the converted digital image data for one screen, window means for setting a window on the image data for one screen and extracting pixel data for a plurality of pixels in the window, A means for generating data on the inclination of the image data, a means for calculating the degree of coincidence between the inclination data and a plurality of edge patterns, a means for calculating an edge-likeness evaluation value from the degree of coincidence, and the edge-likeness It is provided with a means for controlling the calculation of the evaluation value for all pixels of one screen.

According to the present invention, a window is set for image data for one screen, pixel data for a plurality of pixels in the window is extracted, data relating to the inclination of the image data in the window is generated, and The degree of coincidence between the inclination data and the plurality of edge patterns is calculated, the edge-likeness evaluation value is calculated from the coincidence degree, and the edge-likeness evaluation value is calculated for all pixels of one screen. Since the edge image data composed of the above evaluation values is obtained, it is possible to generate a good edge image in which good quality edges are emphasized, and it is possible to remove the influence of noise and the like.

The present invention actually images a sample of an object to be inspected or recognized (measured) under illumination by an illumination device,
A device and method for actually inspecting or recognizing (measuring) a sample based on image data obtained by this imaging, and evaluating the inspection or recognition result to optimize the illumination condition (for example, the luminous intensity of the illuminating device). providing.

First, an illumination condition setting support device and method for a system for inspecting non-defective products and non-defective products will be described.

The lighting condition setting support device according to the present invention is
A sample supply device for sequentially supplying a plurality of samples of non-defective products and defective products to a predetermined observation position, an illumination device with variable illumination conditions for illuminating the sample at the observation position, and a non-defective product brought to the observation position by the supply device, An imaging device that images each defective sample under illumination by the illumination device and outputs a video signal representing the captured sample, and a feature that measures the feature amount of each sample based on the video signal output from the imaging device Quantity measuring means, means for calculating an evaluation value relating to the accuracy of discrimination between non-defective products and defective products based on the characteristic amount measured by the characteristic amount measuring means, and for each illumination condition obtained while changing the illumination condition of the illumination device. Based on the evaluation value, a means for searching for an illumination condition having the best evaluation value is provided.

A lighting condition setting support method according to the present invention comprises:
An illuminating device with variable lighting conditions for illuminating a predetermined observation position is arranged, a plurality of samples of good products and defective products are sequentially supplied to the observation position, and each sample of good products and defective products supplied to the observation position is described above. An image is taken under illumination by an illuminating device, the characteristic amount of each sample is measured based on the image signal obtained by the imaging, and an evaluation value regarding the accuracy of discriminating between a good product and a defective product is calculated based on the measured characteristic amount. While changing the lighting condition of the lighting device, the evaluation value is obtained for each lighting condition, and the lighting condition with the best evaluation value is searched.

According to the present invention, the illumination condition is evaluated from the picked-up images of the actual non-defective product sample and the defective product sample, and the illumination condition that can discriminate the non-defective product from the defective product is searched as reliably as possible. High quality inspection is possible.

Next, a lighting condition setting support device and method for a system for measuring the feature amount of an object will be described.

The lighting condition setting support device according to the present invention is
A sample supply device that sequentially supplies a plurality of samples to a predetermined observation position, an illumination device that illuminates the sample at the observation position and has a variable illumination condition, and each sample brought to the observation position by the supply device is provided by the illumination device. An image pickup device that picks up an image under illumination and outputs a video signal representing the picked-up sample, a feature amount measuring unit that measures the feature amount of each sample based on the video signal output from the image pickup device,
A means for calculating the variance of the feature quantity measured by the feature quantity measuring means, and a variance for each illumination condition obtained by changing the illumination condition of the illumination device are searched for the illumination condition with the minimum variance. Equipped with means.

A lighting condition setting support method according to the present invention comprises:
An illuminator with variable illumination conditions that illuminates a predetermined observation position is arranged, a plurality of samples are sequentially supplied to the observation position, and each sample supplied to the observation position is imaged under the illumination of the illuminating device and imaged. The feature amount of each sample is measured based on the video signal obtained by, the variance of the feature amount of all the measured samples is calculated, and the variance for each illumination condition is obtained by changing the illumination condition of the above lighting device, and the variance is calculated. Is to search for a lighting condition that minimizes.

According to the present invention, a sample of an object to be measured is actually imaged, the feature amount of the sample is actually measured using the image data obtained by this image pickup, and the illumination condition in which the variance of the measured feature amount is small. Since the search is performed, the dispersion of the measured values becomes small, and the measurement can always be performed with high accuracy.

By configuring the sample supply device with a rotary table on which each sample is placed and a drive device for rotationally driving the rotary table, it is possible to simplify the configuration and save space.

Finally, the present invention provides a photographing condition determination support device for determining an appropriate photographing condition by a camera in which a lens and a necessary close-up ring are detachable.

This apparatus includes information on the field of view of the camera, information on the installation distance of the camera with respect to the object to be photographed, information on the lens,
An input device for inputting at least two pieces of information of the close-up ring, an arithmetic device for calculating the remaining information using at least two pieces of information input from the input device, and an arithmetic result by the arithmetic device. A display device is provided for displaying the remaining information represented.

According to the present invention, the visual field information of the camera,
The remaining information is calculated and displayed by inputting at least two pieces of information on the installation distance of the camera to the object to be photographed, information on the lens, and information on the close-up ring. You can select or determine the appropriate lens, close-up ring, camera installation distance, etc.

As for the evaluation and optimization of the imaging conditions (imaging system), as in the case of the evaluation and optimization of the illumination conditions, the object is actually imaged under each of a plurality of kinds of imaging conditions and the imaging is performed. It goes without saying that the evaluation value of the imaging condition can be calculated based on the image data obtained by, and the evaluation value can be calculated based on this evaluation value.

[0044]

【Example】

(1) Types of lighting devices and lighting methods Lighting devices (light sources) used in image processing systems
The main ones are fluorescent lamps and halogen lamps.

Fluorescent lamps are roughly classified into a ring type and a straight tube type according to their shapes, and various sizes are commercially available. Figure 1
Shows a ring type fluorescent lamp 11. FIG. 2 shows a straight tube type fluorescent lamp 12.

In an illuminating device using a halogen lamp as a light source, the light from the halogen lamp is guided to a light irradiating section using an optical fiber called a light guide. A ring type, a slit type, a straight type, a bifurcated type, etc. having various types of light irradiation parts are commercially available.
There are variations in dimensions.

FIG. 3 shows an illuminating device 13 which is a so-called ring light guide and which has a ring-shaped light irradiation section. A large number of optical fibers 17 are bundled, and the light irradiation section is configured by arranging their tips in a ring shape.

FIG. 4 shows an illuminating device 14 which is a so-called slit ring guide. The light irradiation unit is configured by arranging the tips of a large number of optical fibers 17 in a straight line, and is suitable for generating slit light.

FIG. 5 shows an illuminating device 15 for projecting light having a circular cross section from the end of a bundle of a large number of optical fibers 17.
It is called a straight light guide.

In the illuminating device 16 shown in FIG. 6, the bundle of optical fibers 17 is divided into two, and light having a circular cross section is projected from the respective tip portions. This is called a bifurcated light guide.

Particularly, the slit light guide 14, the straight light guide 15 and the bifurcated light guide 16 are suitable when the illumination area is narrow.

The above is summarized as follows. Ring fluorescent lamp 11 (Fig. 1) Straight tube fluorescent lamp 12 (Fig. 2) Ring light guide 13 (Fig. 3) Slit light guide 14 (Fig. 4) Straight light guide 15 (Fig. 5) Bifurcated light・ Guide 16 (Fig. 6)

7 to 11 show various illumination methods described below. Transmitted light illumination (Fig. 7) Uniform light illumination (Fig. 8) Coaxial epi-illumination (Fig. 9) Parallel light illumination (Fig. 10) Dark field illumination (Fig. 11)

The transmitted light illumination (FIG. 7) illuminates the light of the light source 10 from below the diffusion plate 29 on which the object OB is placed. An image pickup device (for example, a CCD television camera) 20 is arranged above the object OB, and this camera 20 is used for the object O.
An image of the light transmitted through the diffuser plate 29 is picked up at a portion other than the portion occupied by B.

The uniform light illumination (FIG. 8) irradiates the object OB with light having a uniform intensity distribution from above the same object OB where the camera 20 is arranged. In FIG. 8, the illumination light is drawn as parallel light, but it need not be parallel light. Uniform light illumination is also called uniform illumination.

In the coaxial epi-illumination (FIG. 9), a half mirror 28 tilted at about 45 ° is arranged between the camera 20 and the object OB. Light is applied to the half mirror 28 from the lateral direction, and the light reflected by the half mirror 28 is applied to the object OB. Half mirror 28 that reflects on the object OB
The light that has passed through is incident on the camera 20. The coaxial epi-illumination means an illumination as if the illumination light is emitted from the camera 20 as an image pickup device.

The collimated light (FIG. 10) illuminates collimated light on the object OB
It is a method of irradiating to In FIG. 10, parallel light is applied to the object OB from diagonally above. This is called parallel illumination. Of course, parallel light may be irradiated onto the object OB from vertically above. Generally, the background BG on which the object OB is placed is composed of a substance that causes diffuse reflection. As a result, both the object OB and the background BG appear bright to the camera 20.

For dark field illumination (FIG. 11), a background BG with a mirror surface or a surface close to it is used. The illumination light is emitted obliquely from above. Diffuse reflected light (diffuse reflected light) from the object OB enters the camera 20. Since the diffused reflection light from the background BG is very small, the background BG looks dark to the camera 20.

(2) Illumination condition decision support device (part 1: Optimum height decision support) The object is illuminated by the illumination device, and the image of the illuminated object is imaged by the image pickup device. In the image processing system that executes image processing such as various inspections using image data, a support device for determining the optimum height of the illumination device with respect to the object will be described.

FIG. 12 shows the overall configuration of an image processing system including an optimum height determination support device.

The image processing system includes a lighting device 11 for illuminating the object OB, a television camera 20 as an imaging device for imaging the object OB, and an image processing device 40.

The ring fluorescent lamp shown in FIG. 1 is used as the illuminating device 11, and the object OB is illuminated from directly above it. The ring center of the fluorescent lamp 11 is located directly above the object OB. The distance between the illumination device 11 and the object OB, that is, the height of the illumination device 11 with respect to the object OB is h. As the illuminating device 11, the ring light guide 13 shown in FIG. 3 can be used.

The lighting device 11 is supported by a column 30 and a supporting device 31 so as to be vertically movable. The support device 31 is a lighting device.
11 gripping parts 32 and a sliding part 33 fixedly connected to the gripping part 32 via an arm. The sliding portion 33 is a tubular body, and the support column 30 slidably penetrates through the hole of the tubular body. Therefore, the sliding portion 33 is supported by the column 30 so as to be vertically movable. A stopper 34 such as a set screw or a set bolt is provided on the sliding portion 33, and the sliding portion 33 is fixed to the column 30 by the stopper 34. Therefore, the lighting device 11 is manually adjusted to an arbitrary height position and fixed.

The camera 20 as an image pickup device is provided with an object OB.
The image pickup center is aligned with the center of the ring of the illuminating device 11 at a position directly above, and the object OB is imaged from above under illumination by the illuminating device 11. The supporting device for the camera 20 is not shown to avoid cluttering the drawing. The camera 20 is fixedly supported by a supporting device. Needless to say, the camera 20 may also be supported so as to be vertically movable.

The image signal representing the object OB photographed by the camera 20 (a monochrome image signal is sufficient, but a color image signal may be used) is the image processing device 40.
Given to. The image processing device 40 is preferably composed of a computer system and has a function as an illumination condition determination support device described later. The image processing device 40 is C
An RT display device 41 is provided. An image of the object OB taken by the camera 20 is displayed on the display device 41, and the optimum height h _P of the lighting device 11 determined by the image processing device 40 is displayed as shown in FIG. The user is notified of the optimum height h _P.

FIG. 13 shows another example of the image processing system. The same components as those shown in FIG. 12 are designated by the same reference numerals to avoid redundant description. In this image processing system, the lighting device 11
Is automatically moved up and down according to a command from the image processing device 40, and is positioned at the optimum height h _P.

The raising / lowering mechanism 38 of the lighting device 11 includes a rack 35 fixed to the sliding portion 33 and a pinion that meshes with the rack 35.
It has 36 and. The pinion 36 is rotatably supported by a fixed bearing (not shown). The pinion 36 is also rotationally driven by a pulse motor 37.

The optimum height h of the illumination device 11 is the image processing device 40.
_{When P} is determined, the device 40 gives a forward or reverse rotation command to the motor 37 so that the lighting device 11 has this height h _P. Since the motor 37 rotates by the commanded rotation amount, the lighting device 11 is moved up and down via the pinion 36 and the rack 35, and is positioned at the position of the optimum height h _P. Lifting mechanism if necessary
38 or the motor 37 is provided with a lock mechanism to hold the lighting device 11 at the optimum height position.

FIG. 14 shows the configuration of an illumination condition determination support device suitable for supporting the determination of the optimum height of the illumination device 11.

The illumination condition determination support device 50 includes a user machine interface 53 and an optimum height determination unit 54. The respective units 53 and 54 are included in the image processing device 40.

The input device 51 is composed of a keyboard, a light pen, a mouse and the like. The output device 52 includes the CRT display device 41 and the pulse motor 37 described above. The user can operate the user machine interface 53 to display the display device.
The input device 51 is operated in accordance with the menus, instructions, marks, cursors, etc. displayed on 41 to interactively input various data and information.

The optimum height h _P determined by the optimum height determination unit 54
Is displayed on the display device 41 (output device 52) or used as a command to the motor 37, as described above. The optimum height determining unit 54 is preferably composed of a CPU that operates according to a program, and a database that will be described later and a memory that stores various input data.

16 to 19 show the optimum installation height of the annular illumination device 13 (for example, a ring light guide illumination device) for the object OB having an annular groove (engraved portion) g formed on the surface. It shows how to determine h _p .

The optimum installation height h _P is the height of the illuminating device 13 with respect to the object OB for obtaining illumination in which the groove g is dark and the surface of the object OB other than the groove g is uniformly bright. Say.

When the illuminating device 13 is installed at a considerably high position as shown in FIG. 16, the light from the illuminating device 13 reaches the bottom surface of the groove g. Is illuminated, and the groove g does not become dark.

On the other hand, when the illuminating device 13 is lowered to a height equal to or less than the upper limit value h1, the illumination light does not reach the bottom surface of the groove g and the groove g becomes dark as shown in FIG. . Therefore, the condition of the height h of the illuminating device 13 for obtaining the illumination state in which the groove g becomes a dark part is given by h ≦ h1.

The upper limit value h1 is expressed by the following equation.

[0078]

## EQU00001 ## h1 = d.times. {(R1-R2) / W} Equation 1

Where d is the depth of the groove g, W is the width of the groove g,
R1 is the distance from the center of the field of view to the furthest edge of the groove g, and R2 is the radius of the illumination device 13.

On the other hand, in order to uniformly illuminate the surface of the object OB other than the groove g, it is necessary to consider the isoilluminance curve of the illuminating device 13 so that the surface of the object OB is not unevenly illuminated. Need to meet.

FIG. 18 shows a ring light guide lighting device 13
Shows the isolux curve of

It can be seen from this figure that the radius R of the area illuminated with equal illuminance changes according to the vertical distance from the illuminating device 13, that is, the installation height h of the illuminating device 13.

FIG. 19 shows the radius R of the area illuminated with equal illuminance.
And the installation height h of the lighting device 13 are shown. The radius of the visual field of the imaging device 20 (the range for illuminating the object) is R0. In Fig. 19, the radius R of the area illuminated with equal illuminance
Is equal to the radius R0 of the visual field, the installation height h of the illuminating device 13 is h0. Therefore, in order to illuminate a portion other than the groove g brightly and uniformly, the lower limit value of the installation height h of the illumination device 13 may be set to h0. This condition is h ≧ h
It is 0.

From the above two conditions, the optimum installation height h _P of the lighting device 13 can be determined within the range of h0 ≦ h _P ≦ h1. Information regarding the radius R2 and the isolux curve for each type of lighting device is stored in the memory in the optimum height determination unit 54 as a data base.

In FIG. 20, the optimum height determining unit 54 is used for photographing the groove g of the object OB having the groove g described above as a dark portion and the surface of the object OB other than the groove g as a uniform bright portion. It shows the procedure of the optimum height determination process of the lighting device to be executed.

First, the depth d of the groove g, the width W, and the distance R1 from the center of the visual field to the furthest edge of the groove g are input by the user from the input device 51 as information regarding the geometrical characteristics of the object OB. Further, the radius R0 of the visual field of the image pickup device 13 is input by the user through the input device 51 (step
201). However, this field-of-view radius R0 may be equal to the radius of the object OB or half the length of its diagonal,
It can also be input as one of the geometrical characteristics of the object OB.

Assuming that the luminaire type has already been entered or determined, the radius R2 of the luminaire is read from the database. Further, the lower limit value h0 of the height is derived from the data base relating to the isoilluminance curve of the illuminating device by using the already input field radius R0 (step 202).

Next, the calculation of the equation (1) is executed to calculate the upper limit value h1 of the installation height of the lighting device (step 203).
). It is determined whether the calculated upper limit value h1 is greater than or equal to the lower limit value h0 (step 204).

If h0 ≦ h1, the optimum height can be determined. Therefore, the average value of the lower limit value h0 and the upper limit value h1 is calculated as the optimum installation height h _P of the lighting device by using the equation 2 (step 205).

[0090]

## EQU00002 ## h _P = (h0 + h1) / 2 Equation 2

The calculation of the optimum height h _P is not limited to the equation 2, but h0
It goes without saying that the height h _P that satisfies ≦ h _P ≦ h1 can be selected as the optimum height.

In this way, the optimum height h _{P determined}
Is output through the output device 52 (step 206). For example, a message image as shown in FIG. 15 is displayed on the display device to inform the user of the optimum installation height h _P of the lighting device.
Displayed at 41. Alternatively, the motor 37 is driven based on this optimum height h _P , and the lighting device is automatically positioned at the position of this height h _P.

If h0≤h1 is not satisfied, a message is displayed on the display device 41 indicating that the optimum height h _P cannot be obtained (step 207).

(3) Illumination condition determination support device (part 2: support for determination of optimum angle) Next, the support device for determining the optimum angle of the illumination device with respect to the object in the image processing system will be described.

FIG. 21 shows the overall structure of an image processing system including an optimum angle determination support device.

A slit light guide 14 shown in FIG. 4 is used as an illuminating device. This illuminating device 14 is held in a horizontal posture in its longitudinal direction, and is arranged so as to illuminate the object OB obliquely from above. As a lighting device, a straight tube fluorescent lamp 12 shown in FIG.
Can also be used.

In FIG. 21, the same parts as those shown in FIG. 12 are designated by the same reference numerals to avoid redundant description. Holding part of the lighting device 14
32A is tiltably held by the sliding portion 33,
14 orientations can be manually set and fixed at any angle.

As in the system configuration shown in FIG. 13, a mechanism for automatically raising and lowering the sliding portion 33 and a mechanism for automatically positioning the gripping portion 32A at an arbitrary angle are provided. It goes without saying that the height and the angle can be automatically set according to the command.

FIG. 22 shows an example of the object OB. The object OB is a plate-like body, and a linear groove G extending in the longitudinal direction is formed on the surface thereof.

FIG. 23 shows the configuration of an illumination condition determination support device suitable for supporting the determination of the optimum installation angle of the illumination device 14. Compared with the configuration shown in Fig. 14, the optimum height determination unit
An optimum angle determination unit 55 is provided instead of 54. Other configurations are the same as those shown in FIG.

24 and 25 show an object O having a groove G.
The method of setting the installation angle θ of the illumination device 14 (slit light guide illumination device) with respect to B to an optimum value is shown.

The optimum installation angle θ of the illuminating device 14 is for obtaining illumination in which the groove G of the object OB is a dark part and the other surface part is a bright part. In order to realize this, when the width of the groove G is S and the depth of the groove G is t, Equation 3
Must meet the relationship. Angle θ is for lighting device 14
It is the angle between the ray (optical axis) from and the horizontal plane.

[0103]

Equation 3 tan θ ≦ t / S Equation 3

On the surface of an ordinary object, incident light on the object is incompletely diffused and reflected as shown in FIG. That is, the intensity of the specular reflection light equal to the incident angle is the strongest, and the intensity of the reflection light decreases as the specular reflection angle deviates. In order to image the surface of the object OB other than the groove G as a bright portion and obtain a clear contrast with the groove G in the dark portion, the image pickup device 20
It is necessary to increase the intensity of the reflected light from the portion other than the groove portion G incident on the. Since the imaging device 20 is installed right above the object OB or at a position close to it, the imaging device 20
In order to allow as many specularly reflected lights to enter as possible, the installation angle θ of the lighting device 14 should be as close as possible to 90 degrees. From this, the optimal installation angle θ of the lighting device 14
Is given by Equation 4.

[0105]

## EQU4 ## θ _P = tan ^-1 (t / S) Equation 4

FIG. 26 shows an object OB having a groove G,
The procedure of the process executed by the appropriate angle determination unit 55 in order to find the illumination condition for imaging the groove G as a dark portion and the other portion as a bright portion is shown.

First, the user inputs the object OB from the input device 51.
Data about the width S and the depth t of the groove G is input (step 211). Next, the calculation of Expression 4 is executed to calculate the optimum installation angle θ _P of the lighting device 14 (step 212).
). The calculated optimum installation angle θ _P is output from the output device 52 (step 213). For example, a message image (not shown) for notifying the user of the optimum installation angle θ _P of the lighting device 14 is displayed on the screen of the display device 41.

(4) Illumination condition determination support device (3: Support for determination of illumination device and illumination method) In an image processing system, in order to obtain an image suitable for an inspection purpose, which illumination device is used Whether to illuminate with such a lighting method is also a very important factor.

The inventors examined in detail what kind of lighting device was used in what kind of lighting method to inspect what and how, and appropriate lighting based on the following three factors. We obtained the knowledge that the device and lighting method can be determined.
That is, there are three factors: the purpose of inspection, the difference in optical properties between the part of interest and the background, and the size of the field of view.

The lighting device and the lighting method can be temporarily determined based on the above factors. Strictly speaking, it is also important to determine which of the differences (transmittance, reflectance, reflection direction, color, etc.) in the optical properties of the part of interest and the background determines the lighting device and lighting method. Is. This is because, in general, the part of interest to be inspected and the background do not differ in any one of transmittance, reflectance, reflection direction, color, and the like.

Therefore, it is necessary to consider factors suitable for each inspection purpose based on the factors. For this purpose, the expert's empirical knowledge and optical analysis results acquired in advance are used.

FIG. 27 shows a configuration example of a lighting condition determination support device suitable for supporting the determination of the lighting device and the lighting method. Compared to FIG. 14 and FIG. 23, the decision unit 54 or
Instead of 55, a lighting device and lighting method determination unit 56 is provided.

FIG. 28 shows the appearance of two connectors as an example of the inspection object (work). This connector will be described later in an example of determining a lighting device and a lighting method.

FIG. 29 shows the overall procedure of the illumination condition determination support device 50 for determining the illumination device and illumination method.

When the user inputs the inspection purpose from the input device 51 through the dialogue using the display screen of the display device 41, the process jumps to any of the processes shown in FIGS. 30 to 36 according to the input inspection purpose. This will be the case (step 221). The relationship between the inspection purpose and these processes is as follows.

Inspection of shape and dimensions Processing of FIG. 30 Inspection of presence / absence of article and processing of FIG. 31 Inspection of scratches Processing of FIG. 32 Color inspection of FIG. 33 Positioning processing of FIG. 34 (A) and (B) Inspection of foreign matter Processing of Figure 35 Processing of character and mark Processing of Figure 36

The size of the field of view may also be entered, as shown in FIG.
As can be seen from the side of the display screen shown in FIG. 43, the illuminating device suitable for the size of the visual field is displayed, so that the user can determine the illuminating device without inputting the size of the visual field. . Of course, after inputting the size of the visual field, only the illumination device suitable for the input size of the visual field may be displayed.

As will be described in detail later, in the concrete processing matching the inspection purpose shown in FIGS. 30 to 36, the difference in the optical properties between the attention area of the factor and the background is sequentially asked on the screen of the display device 41. Then, when the user inputs an answer to the answer through the input device 51, the difference in the optical properties between the optimal attention portion to be noticed for the inspection and the background is derived (step 222), and according to the result. A lighting device and a lighting method are determined (step 223). In this embodiment, the user finally decides the lighting device and the lighting method from some combinations of the lighting device and the lighting method displayed on the displayed screen.

In the determination process for the purpose of inspecting the shape and dimensions shown in FIG. 30, first, it is inquired whether or not silhouette inspection is possible (step 231). When the user inputs an answer that it is possible, since the difference between the optimum optical parts to be inspected for inspection and the optical properties of the background is the transmittance, the transmitted light illumination screen shown in FIG. 37 is displayed on the display device. Displayed at 41 (step 232).

This transmitted light illumination screen shows that the transmitted light illumination shown in FIG. 7 is suitable if the silhouette inspection is possible. There are two types of transmitted light illumination: a type 1 in which an illumination device, an object, and a camera are horizontally arranged, and a type 2 in which these are vertically arranged (arrangement shown in FIG. 7). Common to both of these types, an appropriate lighting device is displayed according to the size of the field of view. The user will select one of these displayed lighting devices that matches the size of the field of view. Where φ is the diameter of the ring type lighting device,
l (lowercase letter L) (see FIG. 38) indicates the length of the linear illumination device.

When the user inputs that the silhouette inspection is not possible, the display device 41 then asks whether or not the color of the target portion is similar to the background color (step 233).
). If the color of the part of interest and the color of the background are not similar, the differences to be noted are the color and reflectance. Then, the screen for uniform light illumination shown in FIG. 38 is displayed (step 234).

On the screen for uniform light illumination, uniform light illumination (FIG. 8)
Is appropriate, and the type of illuminator suitable for various field sizes in uniform light illumination is displayed.

When silhouette inspection cannot be performed and the color of the target portion and the background are similar, the notable difference is the light reflection direction. Then, it is asked whether there is a protrusion or a hole in the part of interest (steps 235 and 237).

If there is a protrusion on the target portion of the target object, FIG.
The uneven projection illumination screen (screen for illumination focusing on the projection of the unevenness) shown in is displayed (step 236). This screen shows that parallel light illumination (Fig. 10) is appropriate and the type of illumination device used in this parallel light illumination is displayed for each size of the field of view.

If there is a hole in the focused portion, the uneven hole illumination screen (for illumination of focusing on the hole among the unevenness) shown in FIG. 40 is displayed (step 238). On this screen, parallel light illumination or coaxial epi-illumination (FIG. 9) is appropriate, and an illuminating device for each size of the visual field suitable for them is displayed according to the purpose or location of the inspection.

When there is no protrusion or hole in the target portion, the uneven edge illumination screen shown in FIG. 41 is displayed (step 239).
). This screen shows that parallel light illumination is appropriate and the type of illumination device according to the size of the field of view.

For the purpose of the inspection shown in FIG. 31 for the presence / absence of parts and the absence of parts, whether or not silhouette inspection is possible (step 241), the color of the parts and the base (main body on which the parts are mounted) Whether the colors are similar (step 24
3) are sequentially queried through the display device 41.

With special reference to other than the illumination screen described with reference to FIG. 30, when the parts and the base have similar colors, the regular reflection illumination screen shown in FIG. 43 is displayed. (Step 245). Illumination using specular reflection includes collimated illumination (FIG. 10) and dark field illumination (FIG. 11). The user can select an illuminating device displayed on this screen in accordance with the illuminating method and the size of the visual field.

The processing shown in FIGS. 32 to 36 is almost the same as that described above, and the contents of the processing can be understood from these drawings. To explain a little about the uneven lighting screen of Fig. 42, which has not been mentioned yet, this screen is shown in Fig. 32.
This is displayed when the silhouette inspection is not possible and the direction of the damage cannot be specified in the illumination shown in (1) for the purpose of inspection of the damage (NO in both steps 251 and 253). Scratches on the surface of the object (thin linear irregularities)
It has been shown that it is appropriate to use collimated illumination to properly image the, and slit light guides or straight tube fluorescent lamps should be selected depending on the size of the field of view.

As described above, the predetermined question and the user's answer to the question are repeated through the display device 41 and the input device 51 according to the inspection purpose, and the optimum attention portion to be noticed for the intended inspection. What is the difference in optical properties between the background and the background is determined, and an appropriate illumination device and illumination method are determined based on the determination result.

As a specific example, the case of inspecting the connector pins for disconnection shown in FIG. 28 will be described. Since the inspection purpose corresponds to the presence / absence of parts and the inspection of missing parts, the process proceeds to the process shown in FIG. If the silhouette line can be inspected on the inspection line, the transmitted light illumination screen shown in FIG. 37 is displayed. Since the field of view is about 30 mm, horizontal or vertical transmitted light illumination using a ring type fluorescent lamp is appropriate. If the silhouette inspection cannot be performed, the process moves to the next determination, and since the colors of the parts and the base are not similar, the uniform light illumination screen shown in FIG. 38 is displayed. In this example, the object is horizontally long (type 2) and the field of view is about 30 mm, so it can be concluded that it is appropriate to illuminate from a diagonally upper position using a slit light guide.

In the above example, the process proceeds by the user interacting with the determination unit 56 through the display device 41 and the input device 51. The processing may be advanced by the user inputting various data and information according to a selection flow for selecting the above factors, and a guidebook. Further, although the selection is made in the order of the factor, the procedure may be such that the "size of the visual field" is first determined.

(5) Illumination condition determination support device (4) As a final example of the illumination condition determination support device, for determining the above-described illumination device and illumination method, and determining the optimal height or optimal angle of the illumination device. The device will be described.

The illumination condition determination support device 50 as shown in FIG. 44 includes the above-described optimum height determination unit 54 and optimum angle determination unit.
55 and a lighting device and lighting method determination unit 56 are provided. Other configurations are the same as those shown in FIGS. 14, 23 and 27.

The processing procedure executed in this device 50 is shown in FIG.

First, as described above, the illumination device and the illumination method suitable for the inspection purpose are determined through the dialogue between the user and the determination unit 56 (step 311). User display device 41
The optimum illuminating device and illuminating method are selected from among those displayed in FIG.

With respect to the illumination device thus determined, it is determined whether the optimum height or the optimum angle should be determined, and one of the determining units 54 and 55 is selected accordingly (step 312). ). In general, it will be necessary to determine the optimum height for a ring-shaped lighting device, and it will be necessary to determine the optimum angle for a linear lighting device. Required information is input according to the optimum height or angle to be determined, and the optimum height h _P or the optimum angle θ _P is determined according to the process shown in FIG. 20 or the process shown in FIG. 26 (step 313). , Whether the result is displayed on the display device 41,
Alternatively, it is given to a height or angle adjusting device (a lifting mechanism or the like) (step 314).

FIG. 46 shows a processing procedure for determining an optimum height for each of a plurality of types (n types) of lighting devices when they are selected. The same steps as those shown in FIG. 20 are designated by the same step numbers and the description thereof is omitted.

A counter i is provided. This counter i is initially set to i = 1 (step 321) and incremented when there is an illumination device that does not satisfy the condition h0 ≦ h1 of step 204. (Step 323
). After inputting various conditions (step 201), the type of the i-th lighting device is input (step 322), and it is determined whether or not the optimum height h _P can be determined for the input lighting device (step 204). . If it can be determined, the optimum height h _P is obtained, and the processing ends. When the optimum heights cannot be determined for all types (n types) of lighting devices (step 324), a message to that effect is displayed and the process ends (step 207). The radius R0 of the uniform illumination field of view of the illuminator may be entered in step 322 for each illuminator type.

(6) Optimal lighting condition setting support device (part 1:
Setting of Position of Lighting Device) In the above-mentioned lighting condition determination support device (No. 1 and No. 2), the optimum height and the optimum angle of the lighting device are determined based on the positional relationship between the lighting device and the inspection object. . Next, a device that determines or assists the determination of the optimum position of the lighting device from the viewpoint of the quality of the image captured by the camera will be described.

Also in this embodiment, the configuration of the image processing system shown in FIG. 12 is applied. The image processing device 40 takes in a video signal representing the object OB picked up by the television / camera 20 and executes image processing described later for supporting the setting of the optimum height of the lighting device 11. CRT display device
41 displays a photographed image of the object OB and also displays a message for advising the position setting of the lighting device 11.

FIG. 47 shows a circuit configuration of the image processing device 40. The image processing device 40 includes an image input unit 61 and an image memory 6
2. The image output unit 63, the microcomputer, the timing control unit 64, etc.

The image input section 61 includes an A / D converter for converting the analog video signal output from the television camera 20 into digital image data, and supplies this digital image data to the image memory 62. The image input unit 61 also includes a histogram generation circuit that generates an image quality histogram representing the image quality in real time with brightness as the horizontal axis based on the input analog video signal. The specific circuit configuration and operation of this histogram generation circuit will be described later.

The image memory 62 stores the image data supplied from the image input section 61 in pixel units. The image output unit 63 includes a D / A converter for converting the image data read from the image memory 62 into an analog video signal, and supplies the converted analog video signal for one screen to the CRT display device 41. As a result, the object O captured by the TV camera 20
The image of B is also displayed on the display device 41.

The microcomputer has a CPU 65 which is a main body of control and calculation, and a ROM 66, a RAM 67, an I / O control unit 68 and the like are connected to the CPU 65 via a system bus. The CPU 65 decodes and executes the program stored in the ROM 66, reads and writes various data from and in the RAM 67, and executes predetermined image processing. I /
A keyboard 69 is connected to the O control unit 68. The key input signal from the keyboard 69 is sent to the CP via the I / O control unit 68.
It is sent to U65.

Under the control of the CPU 65, the timing control section 64 outputs timing signals for controlling the input / output operation of various data to the image input section 61, the image memory 62, and the image output section 63.

FIG. 48 shows a concrete example of the histogram generation circuit provided in the image input section 61.

The CPU 65 sends an address via the CPU bus.
Control the generator 80. Address generator 80
Generates the necessary address signal, control signal and timing signal, and supplies them to each component. Image memory 62
The writing and reading are controlled by a control signal input via the control bus. Image memory 62 according to the address signal input via the address bus
The image data supplied from the data bus is written in and read out from the address. It goes without saying that the address bus, control bus and data bus are also connected to other circuits. In the image memory 62,
Image data for one field (or one frame) is written.

As shown in FIG. 50, a window of 3 × 3 = 9 pixels is set in the image data for one field (or one frame) stored in the image memory 62, as shown in FIG. The pixel at the center of this window is P ₀ ,
The pixels around this central pixel P ₀ are rotated counterclockwise from P ₁ ~
Given the sign of the P _8. The 3 × 3 window moves in the horizontal and vertical scanning directions in the entire screen area.

To set such a window,
Latch circuit 76, 75, 1H delay circuit (shift register)
78, latch circuits 70, 74, 1H delay circuit 71 and latch circuits 72, 73 are provided, and the image data read from the image memory 62 in the order of horizontal and vertical scanning is supplied to these latch circuits and 1H delay circuits. The data is sequentially transferred in the above order. The 1H delay circuits 78, 71 delay the input data by 1H (1 horizontal scanning period) and output the delayed data, and the latch circuits 76, 75, 70, 7
Reference numerals 4, 72 and 73 delay the input data by one pixel clock cycle and output it.

The image data (pixel P ₇ ) read from the image memory 62 and the output image data (pixels P ₆ , P ₅ , P ₀ , P ₄ , P of the latch circuits 76, 75, 70, 74, 72, 73). ₂ , P
₃ ) and the output image data (pixels P ₈ and P ₁ ) of the 1H delay circuits 78 and 71 are given to the incompatibility calculating unit 81. The output image data (center pixel P ₀ ) of the latch circuit 70 is also given to the non-matching degree histogram generating section 82 and the brightness histogram generating section 83.

FIG. 49 shows a configuration example of the incompatibility calculating section 81. The incompatibility calculating unit 81 calculates the conformity (edge conformity; edge-likeness) μ ₁ to μ ₈ of the image data in the window for each of eight types (8 directions) of edge patterns extending vertically, horizontally, and diagonally. MAX calculation of these goodness-of-fit μ _{1 to} μ ₈ (select the maximum one)
To obtain the edge conformance μ, and then * μ (the non-conformance is indicated by writing a bar above μ in the drawing,
In the specification, it will be expressed as * μ. ) = 1−μ, the degree of non-conformity (unlike edge) is obtained.

Eight subtraction circuits 91 to 98 are provided.
The subtraction circuits 91 to 98 are respectively supplied with the image data of the in-window pixels P _{1 to} P ₈ described above. Further, the image data of the central pixel P ₀ is given to all the subtraction circuits 91 to 98. The subtraction circuit 91 calculates the difference between the image data of the pixel P _{1 and} the image data of the central pixel P ₀ (this is q ₁ ). Similarly, the subtraction circuits 92 to 98 operate on the pixel P
The difference between each of the image data of _{2 to} P _{8 and} the image data of the central pixel P ₀ (these are defined as q ₂ to q ₈ ) is calculated. Since the image data represents a monochrome image as described above (in the case of color image data, the brightness data may be extracted), the brightness of each pixel is shown. Therefore, the difference data q _{1 to} q ₈ are the center pixel P _0.
And the brightness difference between the pixels P _{1 to} P ₈ around it. FIG. 51 shows the brightness patterns P _{0 to} P ₈ in the window.
It is shown that brightness patterns (brightness difference patterns) q _{0 to} q _{8 based on} the central pixel in the window are generated from (P _{0 to} P ₈ indicate image data here). .

In this embodiment, eight kinds of edge patterns are represented by a fuzzy model represented by using a membership function. This fuzzy model is a diagram
52 (A)-(H). N is Negative, Z is ze
53. ro and P respectively represent Positive, and the membership function designated by these codes (this is called a label) is shown in FIG.

As shown by the broken line, the membership function N takes a maximum value of 1 when the brightness difference q is smaller than a negative value -q _b and has a minimum value when the brightness value is larger than 0. It takes a value of 0 and takes a value from 1 to 0 which changes linearly in the range from -q _b to 0.

[0156] membership function P, the difference q of brightness takes a minimum value of 0 is the function value is less than zero range, takes a maximum value at a certain positive value q _b greater than the range, the range of 0~q _b Then, it takes a value between 0 and 1 which linearly changes corresponding to the value.

The membership function Z has a minimum function value when the absolute value of the brightness difference q is larger than _a certain value q _a , and has a maximum value of 1 when the absolute value is smaller than q _b . Then, in the range where the absolute value of the brightness difference q is larger than q _b and smaller than q _a , the function value is an intermediate value between 1 and 0 that linearly changes corresponding to the value.

The fuzzy model shown in FIG. 52 (A) is bright in the lower right direction and dark in the upper left direction, and represents an oblique edge pattern in the upper right direction. Figure 52 (B) shows an edge pattern that is bright to the right, dark to the left, and extends vertically. It can be easily understood that the fuzzy models shown in FIGS. 52 (C) to 52 (H) also represent other kinds of edge patterns. Figure 52 (A) to Figure 52 (H)
The direction of the edge pattern is defined as direction 1 to direction 8.

Returning to FIG. 49, the above-mentioned eight-direction edge
Eight edge conformance calculation circuits 111-
118 are provided. Since these edge conformance calculation circuits have the same configuration except the set membership function, the circuit 111 will be described.

The edge conformity calculation circuit 111 is a membership function circuit (hereinafter referred to as MFC: Membership Funct).
ion circuits) 101 to 108 and a MIN circuit 109 for selecting the minimum value of their outputs. The output data q _{1 to} q ₈ of the subtraction circuits 91 to 98 are MF
Input into C101-108 respectively.

The MFCs 101 to 108 have the right side shown in FIG. 52 (A).
Membership functions Z, N or P are set corresponding to the fuzzy model of the edge pattern of direction 1 pointing 45 degrees upward. More specifically, the pixels P ₁ and P
₅ MFC101 and 10 corresponding to the (brightness difference q ₁ of a q ₅₎
5, the membership function Z has pixels P ₂ , P ₃ , P ₄
(Brightness difference q ₂ of, q _3, q ₄₎ corresponding to the MFC102
, 103, 104 have a membership function N, and MFCs 106, 107, 108 corresponding to pixels P ₆ , P ₇ , P ₈ (brightness differences q ₆ , q ₇ , q ₈ ) have a membership function P. ， Each is set.

The MFC 101 calculates and outputs the goodness of fit μ ₁₁ of the input data q ₁ with respect to the membership function Z set therein. When the MFC is composed of a memory storing membership function data, it suffices to read the membership function data corresponding to the input data q ₁ . Similarly, the MFCs 102 to 108 calculate and output the fitness levels μ _{12 to} μ ₁₈ of the input data q _{2 to} q ₈ with respect to the set membership function N, Z or P.

The MIN circuit 109 selects the smallest one of the matching degrees μ _{11 to} μ ₁₈ output from the MFCs 101 to 108 and outputs it as the matching degree μ ₁ of the edge matching degree calculation circuit 111. The larger the value of the goodness of fit μ ₁ (closer to 1), the more appropriate the binarized image is when the binarization of the data of the other pixels in this window is performed with reference to the brightness of the pixel P _0. Will be obtained.

M of the other edge fitness calculation circuits 112 to 118
Membership functions representing the edge patterns shown in FIGS. 52B to 52H are set in the FC. All of the output data q _{1 to} q ₈ of the subtraction circuits 91 to 98 are given to the edge fitness calculation circuits 112 to 118, respectively, and the fitness levels μ _{2 to} μ _{8 are} output from these circuits 112 to 118.
Is obtained.

The MAX circuit 85 includes the edge conformance calculation circuit 11
Select the maximum conformance μ _{1 to} μ ₈ output by 1 to 118 and output it as the conformance μ. Since the largest matching degree obtained when the direction (pixel pattern) of the edge in the window is made to correspond to the direction 1 to the direction 8 (preset pattern), the matching degree μ is
This means that the matching degree of the most matched direction among the directions 1 to 8 is represented.

The fitness μ output from the MAX circuit 85 is
It is given to the subtraction circuit 87. As the other input of the subtraction circuit 87, data representing the logical value 1 output from the 1 generation circuit 86 is applied. The subtraction circuit 87 outputs a value * μ = 1-μ obtained by subtracting the fitness μ from the value 1. This value * μ
Represents the degree of non-conformity (unlike edge) to the most appropriate edge pattern.

The above processing is repeated by scanning the window over all the pixels of the image data for one field (or one frame). Therefore, the degree of non-conformity * μ is obtained for all pixels (for windows in which all pixels are central pixels).

Incompatibility Degree * μ Obtained by Incompatibility Calculation Unit 81
Is provided to the non-fitting degree histogram generating unit 82. Also the non-conforming histogram generator 82, image data of the central pixel P ₀ (representing the brightness of the central pixel P ₀₎ is given as described above. Non-Fitness Histogram Generator 82
For each brightness represented by the image data of the central pixel P ₀ that generated the non-fitness * μ (in the case of 8-bit representation, for each step of 256 steps). And) cumulative addition to generate a non-fitting histogram. In this non-conforming degree histogram, the horizontal axis represents the brightness and the vertical axis represents the added value of the non-conforming degree.

The brightness histogram generator 83 cumulatively adds, for each brightness, the number of reference pixels P ₀ having that brightness based on the image data (brightness) of the given reference pixel P ₀ , Generate a brightness histogram. The horizontal axis of this brightness histogram is brightness (for example, 256 levels), and the vertical axis is the number of pixels with that brightness.

Data representing the non-matching degree histogram generated by the non-conforming degree histogram generating section 82 and the brightness histogram generated by the brightness histogram generating section 83 are given to the image quality histogram generating section 84. The image quality histogram generation unit 84
The cumulative addition value of the non-fitting degree in the non-fitting degree histogram is normalized by dividing by the corresponding number of pixels in the brightness histogram, and the average value of the non-fitting degree * μ is calculated. The image quality histogram shown in FIG. 54 is a histogram formed by plotting the average value of the nonconformity * μ on the vertical axis and the brightness on the horizontal axis. The average value of the non-conformity * μ on the vertical axis represents the poor image quality as the image quality evaluation standard.

In the image quality histogram of FIG. 54, the maximum value is Q _max and the minimum value is Q _min . When the image quality data is binarized with the brightness k _opt that gives the minimum value Q _min as the threshold value, the poor image quality is minimized and the best binary image data is obtained.

The CPU 65 reads the maximum value Q _max and the minimum value Q _min of the poor image quality from the image quality histogram generated by the image quality histogram generating section 84. Further CPU65
Reads the brightness k _opt corresponding to the minimum value Q _min . Thereafter, the CPU 65 searches the image quality histogram centering on the brightness k _opt for the brighter side and the darker side on the horizontal axis, and the value on the vertical axis is first (1-a) × Q _max + a × Q.
_The brightness width WB that exceeds the value of _min is calculated. Where a
Is a positive coefficient smaller than 1 and represents tolerance.

The CPU 65 calculates the evaluation value V of the illumination at the set height h of the illumination device 11 according to the equation 5, and stores the calculation result in the RAM 67.

[0174]

## EQU00005 ## V = (Q _max / Q _min ) WB Equation 5

In Expression 5, Q _max / Q _min represents the depth of the valley in the image quality histogram. The larger this value, the more clearly the edge-like portion and the edge-less portion are separated. The contrast is clear. Since WB is the width of the valley as described above, the larger this value is, the more the illuminance of the illuminator changes and the image quality does not change, that is, the contrast variability is good.

The calculation of the evaluation value V is not limited to the equation 5, but the following equations 6 to 10 can be used.

[0177]

## _EQU6 ## V = Q _max / Q _min Equation 6

[0178]

## EQU00007 ## V = WB Equation 7

[0179]

Equation 8 V = 1 / Q _min Equation 8

[0180]

(9) V = WB / Q _min Formula 9

[0181]

V = (Q _max / Q _min ) × (WB / k _opt ) Formula 10

In particular, Expression 10 gives an evaluation value in consideration of the absolute value of the illuminance fluctuation of the light source and the range of brightness that allows stable image capturing.
In general, the degree of darkening due to deterioration of the light source is proportional to the illuminance at that time, so the absolute value of the illuminance fluctuation due to deterioration is smaller for light sources with lower illuminance. On the other hand, the width WB is constant. Assuming that (Q _max / Q _min ) WB is constant, k _opt should be small. The smaller k _opt is, the larger the evaluation value V is.

FIG. 55 shows the relationship between the installation height h of the illumination device 11 and the illumination evaluation value V. The illumination evaluation value V has a maximum value V _max at a certain installation height h _opt , and the evaluation value V monotonically decreases on both sides thereof. That is, the evaluation value V is 1
It is a convex function with peaks.

Therefore, the height of the lighting device 11 is evaluated by the evaluation value V.
In consideration of the above, the optimum place can be set as follows.

An evaluation value V ₀ is obtained at a certain installation height h0,
Next, when a larger evaluation value V1 (V1> V0) is obtained when the installation height h1 (h1> h0) is increased, in order to set the optimum installation height h _opt , the height is further increased. The height of the illumination device 11 may be adjusted in the direction of increasing h.

On the contrary, when the evaluation value V0 is obtained at a certain installation height h0 and the smaller evaluation value V1 (V1 <V0) is obtained when the installation height is increased to h1 (h1> h0) next time, In order to set the optimum installation height h _opt , the height of the lighting device 11 may be adjusted in the direction of decreasing the installation height h.

The CPU 65 of the image processing device 40 is the object OB.
Is captured by the camera 20, the image quality of the captured image is evaluated based on the image data obtained by A / D converting the video signal output from the camera 20, and an instruction regarding the position setting of the illumination device 11 is displayed on the display device 41. The display assists the user in setting the lighting device 11 at an appropriate position.

56 and 57 show the processing procedure by the CPU 65 as described above.

An initial screen including a message as shown in FIG. 58 is displayed on the CRT display device 41 (step 331).
). The user looks at this initial screen, loosens the stopper 34, positions the lighting device 11 at an appropriate height h0, and stops the stopper 34.
Tighten and fix. The user presses the setting key on the keyboard 69 when the setting of the lighting device 11 is completed.
It will be YES.

The CPU 65 causes the television / camera 20 to pick up an image of the object, and causes the obtained video signal to be taken into the image input section 61 (step 333). If necessary, the captured image is displayed on the display device 41.

In the image input section 61, the captured video signal is A /
After D conversion and conversion into image data, an image quality histogram is generated by the above-mentioned method. The CPU 65 reads the brightness k _opt corresponding to the maximum value Q _max , the minimum value Q _min , and the minimum value Q _min of the poor image quality from the image quality histogram generated by the image quality histogram generation unit 84 (step 334).
). Further, the CPU 65 determines the width WB of the brightness in the valley from the image quality histogram, and the formula 5 or formula 6 to formula 10
Is calculated to calculate the illumination evaluation value V0 and the value is stored in the RAM 67 (step 335).

Subsequently, the CPU 65 causes the display device 20 to display a message as shown in FIG. 59 (step 336). The user looks at this display and manually operates the lighting device 11 to set the initial height h0.
It is moved to an appropriate height position h1 higher than that and fixed. After this, the user operates the setting key, so YES in step 337.
Becomes

The object is imaged, the image data is input, and the image quality histogram is created again based on the input image data (step 338). Based on this new image quality histogram, the illumination evaluation value V1 corresponding to the height h1 is obtained. Is calculated (steps 339 and 340).

The CPU 65 determines the previous (initial state) evaluation value V0.
And this evaluation value V1 are compared (step 341), V
If 1> V0, the previous evaluation value V0 is replaced with the current evaluation value V1.
The current evaluation value V1 is stored in the RAM 67 in order to replace it with (step 342). Further, the message of FIG. 59 is displayed on the display device 41 in order to further increase the height of the lighting device 11 (step 343).

If V1≤V0, the CPU 65 stores the present evaluation value V1 in the RAM 67 and updates the evaluation value (step 344), and in order to lower the height of the illuminating device 11, as shown in FIG.
The message shown in is displayed on the display device 41 (step
345).

When the message of FIG. 59 is displayed, the user changes the lighting device 11 to the height position h1 higher than the previous time. When the message of FIG. 60 is displayed, the user changes the lighting device 11 to the height position h1 lower than the previous time.
After that, the user operates the setting key of the keyboard 69, so that the determination in step 346 is YES and the process returns to step 338. The CPU 65 again takes an image of the object OB with the camera 20,
Repeat the creation of image quality histogram and calculation of evaluation value.

While watching the message displayed on the display device 41 in this way, the user repeats the above procedure while adjusting the installation height of the lighting device 11 up and down and gradually reducing the movement amount. Finally, the message in FIGS. 59 and 60 is switched by just adjusting the height slightly. It means that the vicinity of the installation height at that time is the optimum installation height h _opt . Finally, the user operates the end key of the keyboard 69 (step 347), and the adjustment work is completed.

(7) Optimal lighting condition setting support device (Part 2:
Setting of Position of Lighting Device) The above-described support device for optimum position setting is performed by the user with the lighting device 11
The position of is manually positioned. Next, an embodiment in which the user inputs the moving direction and moving distance (or position) of the lighting device 11 from the keyboard to automatically position the lighting device 11 at the commanded position will be described.

As the image processing system, the one provided with the automatic lifting mechanism shown in FIG. 13 is used. As the configuration of the image processing device 40, the one shown in FIG. 47 is used. The pulse motor 37 is connected to the I / O controller 68 as shown by the chain line. The drive of the motor 37 is controlled by a command from the CPU 65 (or a command from the I / O control unit 68). Figure
The configurations of various circuits shown in FIG. 48 and FIG. 49 are also used as they are.

61 and 62 show the processing procedure by the CPU 65. Also in this figure, the same components as those shown in FIGS. 56 and 57 are designated by the same reference numerals to avoid redundant description.

The processing of steps 331 to 336 in FIG. 61 is the same as that shown in FIG.

Seeing the message shown in FIG. 59, the user inputs the moving direction (up or down) and the moving distance of the lighting device 11 from the keyboard 69 (step 352) and operates the setting key (step 352). 337).

Then, based on the data representing the moving direction and the moving distance input from the keyboard 69, the I / O
The pulse motor 37 is driven via the control unit 68 (step 353). As a result, the lighting device 11 moves in the specified direction for the specified distance and then stops there. After that, the object OB is imaged, the image quality histogram is created, and the evaluation value V1 is calculated (steps 338 to 341).

The user sees the message of FIG. 59 or 60 displayed on the display device 41 and inputs the moving direction and moving distance of the lighting device 11 through the keyboard 69 according to the message (steps 354 and 355). After that, if there is a setting key input, the process returns to step 353 and the drive of the motor 37 is controlled to move the lighting device 11.

While watching the message thus displayed on the display device 41, the user adjusts the installation height of the lighting device 11 up and down by inputting a command from the keyboard 69. When the adjustment is completed, the user operates the end key of the keyboard 69 to end the adjustment work (step
347).

In the two embodiments described above, the moving direction of the lighting device 11 is instructed to the user by visual display using a display device. However, the user is instructed by voice, a different alarm sound depending on the moving direction, and the like. You may instruct.

(8) Optimal lighting condition setting support device (Part 3:
Setting of Position of Lighting Device) An embodiment of a device for automatically setting the height position of the lighting device to the optimum height will be described in detail.

The image processing system shown in FIG. 13 is adopted. The configuration of the image processing device shown in FIGS. 47 to 49 is used. In FIG. 47, the pulse motor 37 is connected to the I / O controller 68.

The control processing procedure by the CPU 65 is shown in FIGS. 63 and 64. Also here, the same processes as those shown in FIGS. 56 and 57 are denoted by the same reference numerals.

First, the rotation angle θ ₁ and the rotation direction of the pulse motor 37 are input from the keyboard 69 (step 36).
2). The moving distance may be input instead of the rotation angle θ ₁ . In this case, the CPU 65 calculates the rotation angle θ ₁ of the motor 37 required to move the lighting device 11 by the input moving distance. The direction of rotation will generally be set up, but may be down.

Thereafter, when the start key is input from the keyboard 69 (step 363), the object OB is imaged under the illumination of the illumination device 11 positioned at the initial height h0, and the image quality histogram is created. The evaluation value V0 is calculated (steps 333 to 335).

Next, the CPU 65 drives the pulse motor 37 to rotate by the angle θ ₁ initially set in the direction input in step 362 to raise or lower the lighting device 11 by a corresponding distance (step 364). The height position of the lighting device 11 is h1. Imaging is performed at this height position h1, an image quality histogram is created, and an evaluation value V1 is calculated (step 33).
9, 340).

The CPU 65 determines whether the absolute value of the difference between the previous evaluation value V0 and the current evaluation value V1 is less than or equal to a predetermined threshold value TH (step 365). NO in this judgment
If so, proceed to 341.

Even if this determination is YES, the angle θ
(The angle updated in step 367) is a predetermined threshold θ
It is determined whether or not _{th is} less than _th , and if NO, the process also proceeds to step 341.

At step 341, the evaluation values V0 and V1 are compared.

If V1> V0, the process returns to step 364, and the pulse motor 37 is rotationally driven in the same direction as the previous time by the same angle θ ₁ as before, and the illuminating device 11 is raised or lowered in the same direction. After that, imaging is performed again and evaluation values are calculated.

If V1≤V0, pulse motor 37
The rotation angle θ of is set to half the value of the previous angle θ ₁ and the rotation direction is set to the opposite direction (step 36
7) Return to step 364. The pulse motor 37 is rotationally driven in the direction opposite to the previous time by the newly set angle θ to move the illuminating device 11 in the opposite direction, the image data is taken in again, and the evaluation value is calculated.

As described above, each time V1≤V0 is determined, the rotation angle θ of the pulse motor 37 is sequentially set smaller and the rotation direction is reversed, and the same procedure is repeated.
As a result, when the determinations in steps 365 and 366 are YES, the lighting device 11 is set to the optimum installation height h _opt . This completes the height position adjusting operation of the lighting device.

(9) Edge Image Generating Device An edge image can be generated using the above-described edge matching fitness μ.

The structure of the image processing apparatus shown in FIG. 48 is adopted as the edge image generating apparatus. Preferably, an image memory 88 is further provided for storing the fitness μ for each pixel.
The incompatibility calculation unit shown in FIG. 49 is also used as it is.
The incompatibility * μ is unnecessary, and only the compatibility μ should be output.

FIGS. 65 (A) to 65 (H) show other examples of fuzzy models representing the edge patterns set in the edge conformance calculation circuits 111 to 118, respectively. The membership function Z is not used here. The membership functions P and N have the shape shown in FIG.

According to the fuzzy model shown in FIG. 65 (A), the MFC 101, 10 of the edge conformance calculation circuit 111 is calculated.
2, the membership function P is MFC105,106
, 107 are set to membership functions N, respectively. A membership function that always outputs the maximum logical value of 1 is set to the other MFCs 104 and 108 regardless of the value of the input data.

Membership functions according to FIG. 65 (B) to FIG. 65 (H) are similarly set in the other edge fitness calculation circuits 112 to 118.

The suitability μ is calculated for each pixel for all the image data constituting one field (or one frame) stored in the image memory 62.
Stored in 88 corresponding locations. As a result, Fig. 66
The image showing the edges of the image as shown in (A) is shown in Fig. 66 (B).
It is generated as shown in. The goodness of fit μ may be converted into binary data by using an appropriate threshold value and then stored in the image memory 88.

(10) Optimal lighting condition setting support device (Part 4:
Mainly Setting Luminous Intensity of Illumination Device) An embodiment of the device that sets or supports the optimal illumination condition based on the image data of the object obtained by imaging again will be described.

FIG. 67 shows the overall structure of an automatic inspection device equipped with an illumination system in which the optimum illumination conditions are set by the optimum illumination condition setting support device, which will be described later in detail. This automatic inspection device includes an illumination device 10, a camera 20, an image processing device 40, and a transport mechanism 45. The transfer mechanism 45 is realized by a transfer conveyor and sequentially transfers a large number of inspection objects OB to predetermined inspection positions.

The illuminating device 10 and the camera 20 are arranged above the inspection position. The camera 20 is the object OB at the inspection position.
Is imaged from directly above, and the image data obtained by the imaging is given to the image processing device 40.

The illumination device 10 is realized by a halogen lamp, for example, and illuminates the inspection object OB at the inspection position from diagonally above. The luminosity of the illumination device 10 is set to an optimum value so as to guarantee the optimum inspection of the object OB, as described later.

In the case of the sample inspection in which the inspection of the object OB by the image processing device 40 is a non-defective product or a defective product having a chip or a burr, the discriminating accuracy between the non-defective product and the defective product is maximum. The luminosity of the lighting device 10 is set so that This is the optimum lighting condition.

The illumination condition is not limited to the light intensity, and may be the set position or the set angle of the illumination device 10. Further, the optimum illumination condition may be set in the image processing device 40,
It may be set in a controller incorporated in the lighting device 10. In any case, the illuminating device 10 is controlled by the image processing device 40 or the controller so that the illuminating device 10 performs the illumination that satisfies the set optimal illumination condition.

The image processing device 40 binarizes the video signal representing the object OB given from the camera 20, and
Based on the process of measuring the feature amount such as the area of the target object using the value image data and comparing the measured value with a predetermined reference value, whether the target object OB is a non-defective product, chipping, burr, etc. Determine if it is a defective product. The feature amount that is the basis of the determination is not limited to the area, and may be the perimeter or the center of gravity.

68 and 69 show an apparatus for assisting in setting the optimum illumination condition. The illumination device 10, the camera 20, the image processing device 40, the display device 41 and the like are shown by the same reference numerals as those in the inspection device shown in FIG. 67 for simplification. This is because the inspection device and the optimum illumination condition setting support device can be used together. Of course, both of these devices may be configured separately.

The camera 20 is arranged directly above the observation position OV and at the same height as that in the automatic inspection apparatus.
Further, the illumination device 10 is arranged diagonally above the observation position OV and at the same height position as in the automatic inspection device and at the same inclination angle. The same camera and lighting device are preferably used for the automatic inspection device and the support device.

The support device is equipped with a sample supply mechanism. This sample supply mechanism includes a rotary table 120, a table drive mechanism 121, and a detector 123.

The rotary table 120 is in the shape of a disk and has a non-defective sample OBa, a defective defective sample OBb having a chip, and a defective defective sample OB having a burr on the peripheral portion of the upper surface thereof.
A plurality of c and a plurality of c are positioned and fixed at equal angular intervals.

On the rotary table 120, on the outside of the fixed position of each sample, an identification member 122a made of a metal plate,
122b and 122c are fixed. These identifiers 122
a, 122b, 122c are samples OBa, OBb, OB
This is for causing the detector 123 to detect that c has reached the observation position OV. The installation height of the identifier 122a for the non-defective sample OBa, the installation height of the identifier 122b for the defective defective sample OBb, and the installation height of the identifier 122c for the defective defective sample OBc with burrs are mutually Is different.

The table drive mechanism 121 includes the rotary table 12
An image processing apparatus including a motor connected to the center of rotation of 0
In response to the control signal from 40, the rotary table 120 is intermittently rotated to sequentially guide the samples OBa, OBb, OBc to the observation position OV within the visual field of the camera 120.

The detector 123 is for detecting the non-defective sample OBa that has reached the observation position OV, the defective defective sample OBb having a chip, and the defective defective sample OBc having a burr by distinguishing them from each other. It is located outside.

This detector 123 has three proximity switches 123.
a, 123b, 123c, and the first proximity switch 123a is an identifier for a non-defective sample OBa 1
In order to detect 22a, at the same height position as the identification body 122a,
The second proximity switch 123b is located at the same height as the identifier 122b for detecting the identifier 122b of the defective defective sample OBb, and the third proximity switch 123c is a defective defective sample OBc with burrs. In order to detect the discriminator 122c of the above, the discs are installed at the same height as the discriminator 122c. Each proximity switch 123
Reference numerals a, 123b, and 123c give detection signals to the image processing apparatus 40 when detecting the identification objects 122a, 122b, and 122c, respectively.

FIG. 70 shows the circuit configuration of the image processing device 40. The A / D converter 131, the binarization processing part 132 and the display device are shown in FIG.
41. Sync signal generator 133, CPU 130, ROM 135, R
It is composed of an AM 134, an external storage device 136, and the like.

The A / D converter 131 converts the analog video signal output from the camera 20 into digital image data. The binarization processing unit 132 binarizes the digital image data supplied from the A / D converter 131 with a predetermined threshold value. The display device 41 displays a binarized image represented by the binarized image data. Sync signal generator 133
Generates a vertical synchronizing signal, a horizontal synchronizing signal, and other timing signals, and supplies these signals to the A / D converter 131, the binarization processing unit 132, and the CPU 130.

The CPU 130 is a main body for executing control and calculation for searching and determining the optimum illumination condition, receives the detection signal from the detector 123, and
10. Controls the operation of the table drive mechanism 121 and the like. RO
A program is stored in M135, and various data is temporarily stored in RAM134. The external storage device 136 is configured by a floppy disk device or the like, and stores the determined optimum lighting condition of the lighting device 10 and the like.

FIG. 71 shows a processing procedure by the CPU 130 for determining the optimum illumination condition of the illumination device 10.

First, the number N _{a of} non-defective samples OBa arranged on the rotary table 120, the number N _b of defective defective samples OBb, and the defective sample OBc with burrs.
The number N _c of each is input from the keyboard (step 371). When the start command is given, the image processing device 40 gives a start signal to the table drive mechanism 121.
The rotary table 120 rotates (step 372).

When any of the samples reaches the observation position OV, the first proximity switch 123a if the sample is a good sample OBa, the second proximity switch 123b if the defective sample OBb is defective, If it is a certain defective sample OBc, the third proximity switch 123c detects the corresponding identifiers 122a, 122b, 122c and gives a detection signal to the image processing device 40 (step 173).
).

When this detection signal is input, the CPU 130 outputs a stop signal to stop the table drive mechanism 121,
Stop rotation of the turntable 120 (step 374). As a result, the sample is positioned within the field of view of the camera 20 at the observation position OV.

In this embodiment, the luminous intensity of the lighting device 10 is optimized. The illumination device 10 is given an initial light intensity from the image processing device 40, and the illumination device 10 emits light at this initial light intensity,
Illuminating the sample. The sample of the observation position OV is imaged by the camera 20 under the illumination of the illumination device 10 (step 375). The image signal output from the camera 20 is an image processing device.
Enter 40.

This video signal is A / D converted and binarized. The CPU 130 measures the characteristic amount of the sample at the observation position OV using this binary image data (step 37).
6). In this embodiment, the feature amount is the area of the sample on the captured image. The measured feature amount is stored in the RAM 134.

The RAM 134 is provided with areas for separately storing characteristic quantities for non-defective products, defective products with defects, and defective products with burrs. The CPU 130 determines the observation position OV based on the detection signal input from the detector 123.
It is determined whether the sample is a non-defective sample, a defective defective product having a chip, or a defective defective product having burrs, and the measured feature amount is stored in the storage area for the determined type of sample.

The processing of steps 372 to 376 is a rotary table.
This is done sequentially for all 120 samples.
The number of times the processing is performed is the total number N of the previously input samples.
_a + N _b + N reaches if the turntable to _c 120 will be one rotation (step 377).

When the measurement of the characteristic amount (area) is completed for all the samples on the rotary table 120, the RAM 134
The sum of each type of sample of the stored measured area within the sample number N _a, by dividing each by N _b or N _c, the average value S of area of good sample OBa
_a , the average value S of the areas of defective defective samples OBb
_b and the average value S _c of the area of the defective sample OBc with burrs are obtained (step 378).

Using these average values S _a , S _b and S _c , the evaluation value S of the accuracy of discriminating between the good product and the defective product is calculated by the following equation (step 379).

[0253]

[Equation 11] S = | S _c −S _a | + | S _a −S _b |

The larger the evaluation value S, the higher the accuracy with which a good product and a defective product can be discriminated.

The evaluation value calculation process shown in FIG. 71 is repeated a plurality of times while changing the initial luminous intensity set in the illumination device 10. The horizontal axis represents the initial luminous intensity and the vertical axis represents the calculated evaluation value S.
Similar to the evaluation value V shown in 55, the evaluation value S is a convex function having one peak. Therefore, the initial luminous intensity that gives the evaluation value at or near the maximum value indicates the illumination condition that allows the good product and the defective product to be distinguished with the highest accuracy. Such initial luminous intensity is determined by the CPU 130 or the operator.

The optimum illumination condition (optimum initial luminous intensity) thus determined is stored in the external storage device 136 together with other necessary data. The optimum illumination condition is used in the inspection device shown in FIG.

(11) Optimal lighting condition setting support device (Part 5:
Mainly Setting Luminous Intensity of Illumination Device) In the above embodiment, the optimal illumination condition is set based on the area of the sample. Next, based on the idea that the illumination condition that minimizes the variance of the sample feature amount is optimal, an apparatus that sets or supports the optimal illumination condition will be described.

The illumination system optimized based on the above idea is used in an automatic measuring device for measuring the feature amount such as the position of the center of gravity, the area and the perimeter from the imaged image of the object to be measured.
The configuration of this automatic measuring device is the same as that shown in FIG.

72 and 73 show the configuration of the optimum illumination condition setting support device. The same parts as those shown in FIGS. 68 and 69 are designated by the same reference numerals to avoid redundant description.

A plurality of samples OB _s are positioned and fixed at equiangular intervals on the peripheral portion of the upper surface of the disk-shaped rotary table 120. On the outside of the fixed position of each sample OB _s, an identification body 122 made of a metal plate is arranged at the same height. On the other hand, on the outside of the rotary table 120, a detector 123 composed of a proximity switch is arranged in the vicinity of the observation position OV at the same height as the identification body 122.

The configuration of the image processing device 40 is the same as that shown in FIG. 70, and its illustration and description are omitted.

The processing procedure for determining the optimum illumination condition for measurement is basically the same as that shown in FIG. The differences from the processing in FIG. 71 will be mainly described below. In this embodiment, the number of samples OB _s fixed on the rotary table 120 is input in the first step 371.

The rotary table 120 is rotated, and when any of the samples OB _s reaches the observation position OV, the rotary table 12 is rotated.
0 is stopped and the sample OS _s is imaged. The image processing device 40 sets a predetermined initial luminous intensity in the lighting device 10.

The image processing device 40 processes the image data taken in from the camera 20 to measure the characteristic amount such as the position of the center of gravity and the area, and stores the measured characteristic amount.

The above operation is executed for all samples on the turntable 120.

When the measurement for all the samples OB _s is completed, the variance of the feature amount for all the measured samples is obtained. The smaller the variance is, the smaller the variation of the feature amount is, and the higher the measurement accuracy is.

Similar measurement and calculation of variance are executed while the light intensity of the illuminating device 10 is changed by the image processing device 40. The luminosity that minimizes the obtained dispersion is searched, and the luminosity is determined as the optimum illumination condition.

Although a rotary table is provided in both of the above-mentioned two embodiments, a belt conveyer as shown in FIG. 67 may be used to place and carry the sample.

(12) Imaging Condition Determination Supporting Device Finally, a device for supporting the selection of the lens included in the imaging system, the determination of the installation distance of the camera with respect to the object, and the like will be described.

FIG. 74 shows the structure of the imaging condition determination support device 50. The same parts as those shown in FIG. 14 are designated by the same reference numerals. Since the support device 50 can be realized by using the same image processing device as the support device shown in FIG. 14, the same reference numeral 50 is attached for convenience.

The lens selection unit is included in the imaging condition determination support device 50.
57 are provided. The lens selection unit 57 guides a lens, a close-up ring, an installation distance, etc. suitable for this according to information input by the user from the input device 51, for example, a desired size of the field of view, a desired installation distance, and what is prioritized. .

The relationship between various parameters of the image pickup system will be described with reference to FIG.

Installation distance of the camera 20 (The distance A between the image pickup object OB and the camera 20 is given by the following equation.

[0274]

[Equation 12] A = (Ls (F + B−h−ΔH + d) / Lc) + B−h + d Formula 12 Here, Ls: size of visual field F: flange back B: total length of lens 22 h: first from lens tip Distance to principal point ΔH: principal point distance d: helicoid feeding amount Lc: effective screen of image sensor

The helicoid extension amount d is expressed by the following equation using the focal length fo of the lens 22 (combined lens or lens barrel).

[0276]

D = (Lc × fo / Ls) −FB−h + ΔH + fo Equation 13

The installation distance A of the camera is calculated from Equation 13 as Ls / Lc.
By deriving and substituting it into Eq. 12, it is also expressed as follows.

[0278]

A = fo [(F + d + B−h−ΔH) / (F + d + B−h−ΔH−fo)] + d + B−h Equation 14

The visual field Ls is derived from the equations 13 and 14 as follows.

[0280]

Ls = Lc (A−d−B + h) / (F + d + B−h−ΔH) Equation 15

Since the flange back F and the effective screen Lc of the image pickup device are constants determined by the camera 20, they may be considered as fixed values. Since the total lens length B, the distance h from the lens selection to the first principal point, the principal point interval ΔH, and the actual focal length fo are constants determined by the lens 22, the set of these constants will be expressed as lens. The constant length is uniquely determined by the type of lens.

Then, the equations 12 and 13 are given by the function f ().
The following symbols are simply expressed as follows.

[0283]

## EQU16 ## A = f (Ls, d, lens) Expression 16

[0284]

D = f (Ls, lens) Expression 17

Derivation of d from Equation 14 gives the helicoid feed amount as follows.

[0286]

D = f (A, lens) Equation 18

Further, from Expression 15, the size Ls of the visual field is also expressed as follows.

[0288]

Ls = f (A, d, lens) Equation 19

Expressions 16 to 17 represent the relationship among the camera installation distance A, the size Ls of the visual field, the helicoid extension amount d, and the lens constant length. If at least two of the above four parameters are given by using such a relational expression, the remaining two are determined.

A process of selecting the optimum lens type when the desired size Ls _{0 of the} visual field and the desired installation distance A ₀ are given will be described by using the relationships of the expressions 16 to 19. It is assumed that there are N types of lenses, and the constant length of these lenses is known in advance. Preferably, this lens constant lens is stored in advance in a memory for each type of lens. The user may input the lens constant lens each time.

FIG. 76 shows the processing for prioritizing the desired visual field Ls ₀ .

First, the user inputs the desired field of view Ls ₀ and the desired installation distance A ₀ from the input device 51 (step 38).
0).

The lens constant lens of the first lens (n = 1) is read from the memory or input through the input device 51, and using the desired field of view Ls ₀ and the nth lens constant lens, the expression 17 The helicoid feed amount d is calculated from (steps 381 to 383).

Since the helicoid feed amount d must be smaller than the maximum helicoid feed amount d _max, it is judged whether or not the calculated helicoid feed amount d is larger than the maximum feed amount d _max (step 384).

If the calculated payout amount d of the helicoid is larger than the maximum payout amount d _max , a close-up ring having a thickness t that satisfies the inequality shown in the following equation 20 must be used. A close-up ring with a thickness of 20 is selected (step 385). The data regarding the close-up ring is also preferably stored in advance in the memory.

[0296]

[Equation 20] t <d <(t + d _max ) Expression 20

Next, using the calculated helicoid feeding amount d, the camera installation distance A for the lens is calculated according to the equation 16 (step 386).

The above processing is repeated for N kinds of lenses (steps 387 and 388) and the lens number n, the close-up ring thickness t and the installation distance A obtained in each processing are stored in the memory.

[0299] When the processing of the N types of lenses is completed, from among these lenses, lens number n ₀ with the closest installation distance A to the installation distance A ₀ of the desired is selected (step 289). If there is data on the close-up ring thickness t for the selected lens number n ₀ , it is also selected. The calculated camera installation distance A is the actual camera
20 is the distance to install. It is needless to say that such a lens needs to be selected because the relationship B + d <A must be naturally established among the total length B of the lens 22, the helicoid feeding amount d, and the camera installation distance A. Absent.

The type of lens thus selected, the thickness of the close-up ring, and the installation distance A are displayed on the marking device 41 as shown in FIG.

FIG. 77 shows a process for prioritizing a desired installation distance. The same processes as those shown in FIG. 76 are designated by the same reference numerals to avoid redundant description.

Using the desired installation distance A ₀ and the lens constant length of the nth lens, the helicoid feed amount d is calculated according to the equation 18 (step 383). d>
close-up ring thickness t is calculated in the case of d _{ma x} (step 385).

The field of view Ls is calculated according to equation 19 using the calculated helicoid feed amount d (step 391).

The above processing is repeated for all types of lenses. Then, the lens having the field of view Ls closest to the desired field of view Ls ₀ is selected (step 392).
), The selection result is displayed as shown in FIG. 78 (step 393).

Finally, the process of obtaining the close-up ring and the installation distance for realizing the desired field of view with the designated lens will be described. No particular flow chart is shown for this process.

In this case, since the lens 22 is known, the desired field of view Ls ₀ and the lens constant lens designated are substituted into equation 17 to calculate the helicoid feed amount d. The helicoid extension amount d must be smaller than the maximum helicoid extension amount d _max of the lens. Therefore, when the calculated helicoid extension amount d is larger than the maximum extension amount d _max , the thickness that satisfies the inequality of Eq. A close-up ring of t is used.

Next, using the calculated helicoid feed amount d, the desired visual field Ls ₀ and the lens constant lens, the expression 16 is obtained.
Thus, the installation distance A is obtained.

Also in this case, naturally, the relation B + d <A must be established between the total length B of the lens, the helicoid feed amount d, and the camera installation distance A. Therefore, when B+d> A, it is specified. It means that the desired field of view cannot be realized with the given lens.

As described above, when the desired field of view Ls ₀ and the desired installation distance A ₀ are input from the input device 51, the recommended values are the lens (focal length), the thickness of the close-up ring, and the installation distance displayed on the CRT. Displayed on the device. Further, if the desired field of view and the lens are input, the installation distance A suitable for them is calculated and displayed.

[Brief description of drawings]

FIG. 1 is a perspective view showing a ring fluorescent lamp.

FIG. 2 is a perspective view showing a straight tube fluorescent lamp.

FIG. 3 is a perspective view showing a ring light guide.

FIG. 4 is a perspective view showing a slit light guide.

FIG. 5 is a perspective view showing a straight light guide.

FIG. 6 is a perspective view showing a bifurcated light guide.

FIG. 7 shows transmitted light illumination.

FIG. 8 shows uniform light illumination.

FIG. 9 shows coaxial epi-illumination.

FIG. 10 shows collimated illumination.

FIG. 11 shows dark field illumination.

FIG. 12 shows the overall configuration of an image processing system.

FIG. 13 shows another example of the image processing system.

FIG. 14 is a block diagram showing a configuration of an illumination condition determination support device suitable for supporting determination of an optimum height of the illumination device.

FIG. 15 shows a display example of the determined optimum height on the display device.

FIG. 16 is a view for explaining a method of determining an optimum installation height of a lighting device.

FIG. 17 is a view for explaining a method of determining an optimum installation height of a lighting device.

FIG. 18 shows an illuminating device and an isolux curve of its illuminating light.

FIG. 19 is a graph showing the relationship between the radius of a region illuminated with equal illuminance and the installation height of the illumination device.

FIG. 20 is a flow chart showing a procedure of optimum height determination processing.

FIG. 21 shows still another example of the image processing system.

FIG. 22 is a perspective view showing the shape of an object and the positional relationship between the object and the lighting device.

FIG. 23 is a block diagram showing a configuration of an illumination condition determination support device suitable for supporting optimum angle determination.

FIG. 24 illustrates a method for determining an optimum installation angle of a lighting device.

FIG. 25 shows a state of incomplete diffuse reflection.

FIG. 26 is a flow chart showing a procedure of optimum angle determination processing.

FIG. 27 is a block diagram showing a configuration of an illumination condition determination support device suitable for supporting determination of an illumination device and an illumination method.

FIG. 28 is a perspective view showing the appearance of a connector as an example of an object.

FIG. 29 is a flow chart showing an overall procedure of a process of determining a lighting device and a lighting method.

FIG. 30 is a flow chart showing a processing procedure for determining an illumination device and an illumination method for the purpose of inspecting a shape and dimensions.

FIG. 31 is a flow chart showing a processing procedure for determining an illumination device and an illumination method for the purpose of inspecting the presence / absence of a component or a missing item.

FIG. 32 is a flow chart showing a processing procedure for determining an illumination device and an illumination method for the purpose of inspecting a flaw.

FIG. 33 is a flow chart showing a processing procedure for determining an illumination device and an illumination method for the purpose of color inspection.

34 (A) and (B) are flow charts showing a processing procedure for determining an illumination device and an illumination method for the purpose of positioning.

FIG. 35 is a flow chart showing a processing procedure for determining an illumination device and an illumination method for the purpose of inspecting a foreign substance.

FIG. 36 is a flowchart showing a processing procedure for determining a lighting device and a lighting method for the purpose of inspecting characters and marks.
It is a chart.

FIG. 37 shows a display example of a screen for transmitted light illumination.

FIG. 38 shows a display example of a screen for uniform light illumination.

FIG. 39 shows a display example of an uneven projection illumination screen.

FIG. 40 shows a display example of an uneven hole illumination screen.

FIG. 41 shows a display example of an uneven edge illumination screen.

FIG. 42 shows a display example of a screen for uneven line illumination.

FIG. 43 shows a display example of a screen for illumination using regular reflection.

FIG. 44 is a block diagram showing a configuration of an apparatus suitable for supporting determination of an illumination device and an illumination method, and determination of an optimum height or an optimum angle.

FIG. 45 is a flow chart showing an entire illumination device and illumination method, and an optimum height or optimum angle determination process.

FIG. 46 is a flow chart showing a procedure for determining an optimum height when there are a plurality of lighting devices.

FIG. 47 is a block diagram showing a circuit configuration of an image processing device in the optimum illumination condition setting support device.

FIG. 48 is a block diagram showing a circuit configuration of a histogram generation circuit.

FIG. 49 is a block diagram showing a circuit configuration of an incompatibility calculation unit.

FIG. 50 shows a window set on an image.

FIG. 51 is a diagram for explaining the operation of a subtraction circuit that converts brightness data into data representing a difference in brightness.

52 (A) to (H) show fuzzy models representing edge patterns.

FIG. 53 is a graph showing a membership function.

FIG. 54 is a graph showing an image quality histogram.

FIG. 55 is a graph showing the relationship between the installation height of a lighting device and the evaluation value of lighting.

FIG. 56 is a flow chart showing a procedure for setting the height position of the lighting device.

FIG. 57 is a flowchart showing a procedure for setting the height position of the lighting device.

FIG. 58 shows a display example of a display screen for instructing height setting.

FIG. 59 shows a display example of a display screen for instructing height setting.

FIG. 60 shows a display example of a display screen for instructing height setting.

FIG. 61 is a flowchart showing another example of the height position setting process of the lighting device.

FIG. 62 is a flowchart showing another example of the height position setting process of the lighting device.

FIG. 63 is a flow chart showing still another example of the height position setting process of the illumination device.

FIG. 64 is a flow chart showing still another example of the height position setting process of the lighting device.

65A to 65H show another fuzzy model representing an edge pattern.

66A and 66B show how an edge image is generated from a gray image.

FIG. 67 shows the overall structure of an automatic inspection device.

[Fig. 68] Fig. 68 shows an overall configuration of an optimum illumination condition setting support device.

FIG. 69 is a plan view showing an arrangement state of samples on the rotary table.

FIG. 70 is a block diagram illustrating a circuit configuration example of an image processing device.

71 is a flow chart showing a processing procedure for determining the optimum illumination condition of the illumination device. FIG.

FIG. 72 is a diagram showing an overall configuration of an optimum illumination condition setting support device.

FIG. 73 is a plan view showing the arrangement of samples on the turntable.

FIG. 74 is a block diagram showing a configuration of an imaging condition determination support device.

FIG. 75 is for explaining parameters of a camera, a lens and the like.

FIG. 76 is a flow chart showing a processing procedure for supporting determination of imaging conditions.

FIG. 77 is a flow chart showing another processing procedure for supporting determination of imaging conditions.

[Fig. 78] Fig. 78 is a display example showing selected imaging conditions.

[Explanation of symbols]

 11 Lighting device 20 Television / camera 30 Support 31 Support device 38 Lifting mechanism 41 Display device 61 Image input unit 65 CPU 68 I / O control unit 82 Incompatibility histogram generation unit 83 Brightness histogram generation unit 84 Image quality histogram generation unit

Continuation of front page (31) Priority claim number Japanese Patent Application No. 4-171613 (32) Priority Day 4 (1992) June 4 (33) Country of priority claim Japan (JP) (72) Inventor Shiro Fujieda Omron Co., Ltd. 10 Hanazono Dodo-cho, Ukyo-ku, Kyoto City, Kyoto Prefecture

Claims (19)

[Claims] 1. A lighting device (11) for illuminating an object, and a supporting device (30, 31, for supporting the lighting device in a positionally adjustable manner).
38), an image pickup device for picking up an image of an object under illumination by the above illumination device and outputting a video signal representing an image of the object (2
0), an image quality histogram generation circuit means (6) for generating an image quality histogram representing the degree of quality of image quality with respect to brightness based on the video signal output from the image pickup device.
1, 82, 83, 84), an evaluation value calculation circuit means (65) for calculating an evaluation value of illumination based on the image quality histogram generated by the image quality histogram generation circuit means, and the evaluation value calculation circuit means Illumination including comparison circuit means (65) for comparing the current evaluation value with the previous evaluation value before the position change of the lighting device, and output means (41, 68) for outputting the comparison result by the comparison circuit means. Condition setting support device. 2. The device according to claim 1, wherein said output means is a display device (41) for instructing a position adjustment direction of said lighting device according to a comparison result by said comparison circuit means. 3. A display for indicating the position adjusting direction of the illuminating device according to the comparison result by the comparing circuit means, wherein the supporting device includes a driving device (37) for changing the position of the illuminating device. An input device (69) which is a device (41) and which inputs a command for driving the drive device;
The device according to claim 1, further comprising: a control device (65, 68) for controlling the drive device in response to a command input through the input device. 4. The position of the illuminating device includes a driving device (37) for changing the position of the illuminating device, which controls the driving device (37) according to a comparison result by the comparison circuit means. Control means (65, 6
The device of claim 1, further comprising 8). 5. The image quality histogram generation circuit means includes:
A / D for converting the video signal into digital image data
A conversion means (61), an image memory (62) for storing A / D-converted digital image data for one screen, a window is set for the image data for one screen, and a plurality of pixels in the window are set. Window means (70 to 76, 78) for extracting pixel data, means (91 to 98) for generating data relating to the inclination of the image data in the window, and a degree of matching between the inclination data and a plurality of edge patterns. Means for calculating (101 to 109, 111 to 118)
), Means for calculating the evaluation value of image quality from the degree of matching (8
5, 86, 87), and control the calculation of the image quality evaluation value to be performed for all pixels of one screen, and calculate the average value of the evaluation values for each brightness represented by the image data of each pixel. Device according to claim 1, comprising means (65, 80, 82, 83, 84) for 6. A lighting device (11) for illuminating an object, and a supporting device (30, 31, for supporting the lighting device in a positionally adjustable manner).
38), and an image processing system including an image pickup device (20) for picking up an image of an object under illumination by the illumination device and outputting an image signal representing the image of the object, the image signal output from the image pickup device. Based on, generate an image quality histogram showing the quality of image quality with respect to brightness,
In the image system, an evaluation value of illumination is calculated based on the generated image quality histogram, the calculated evaluation value this time is compared with the previous evaluation value before the position change of the lighting device, and the comparison result is output. Lighting condition setting support method. 7. An image pickup device (20) for picking up an image of an object and outputting a video signal representing a picked-up image, and an A / D conversion means (61) for converting the video signal output from the image pickup device into digital image data. ), An image memory (62) for storing A / D-converted digital image data for one screen, a window is set for the image data for one screen, and pixel data for a plurality of pixels in the window are extracted. Window means (70 to 76, 78) for generating, data generating means (91 to 9) relating to the inclination of the image data in the window
8) Means (101 to 109, 11) for calculating the degree of coincidence between the data relating to the inclination and a plurality of edge patterns, respectively.
1 to 118), means for calculating an edge-likeness evaluation value from the matching degree (85), and means for controlling the edge-likeness evaluation value to be calculated for all pixels of one screen (65, 80). ), And an edge image generating device. 8. The apparatus according to claim 7, further comprising an edge image memory (88) for storing the edge-likeness evaluation value. 9. The apparatus according to claim 7, further comprising means for level-discriminating the edge-likeness evaluation value by a predetermined threshold value and binarizing it. 10. A method for imaging an object by an imaging device (20) and generating data representing an edge image of the captured image based on a video signal representing the captured image obtained by the imaging device (20). The signal is A / D converted into digital image data, a window is set for the image data for one screen, pixel data for a plurality of pixels in the window is extracted, and data regarding the inclination of the image data in the window is extracted. To calculate the degree of coincidence between the data relating to the inclination and a plurality of edge patterns, calculate the edge-likeness evaluation value from the degree of coincidence, and perform the calculation of the edge-likeness evaluation value for one screen. An edge image generation method in which the edge image data consisting of the above evaluation values is obtained for each pixel. 11. A sample supply device (120) for sequentially supplying a plurality of samples of good products and defective products to a predetermined observation position.
, 121), an illumination device (10) with variable illumination conditions for illuminating the sample at the observation position, and images of non-defective and defective samples brought to the observation position by the supply device under illumination by the illumination device. Then, an image pickup device (20) for outputting a video signal representing the sampled image, a feature amount measuring means (130) for measuring the feature amount of each sample based on the video signal output from the image pickup device, and the feature amount measurement. Based on the evaluation value for each lighting condition obtained by changing the lighting condition of the lighting device (130), which calculates an evaluation value related to the accuracy of discrimination between the non-defective product and the defective product based on the characteristic amount measured by the means. A lighting condition setting support device comprising means (130) for searching for a lighting condition having the best evaluation value. 12. The detection device (123, 123a, 123b, 123c) for detecting the presence / absence of a sample supplied to the observation position and the distinction between a non-defective product and a defective product, according to claim 11. Equipment. 13. The sample supply device comprises a rotary table (120) on which each sample is placed, and a drive device (121) for rotationally driving the rotary table (120). The described device. 14. An illumination device (10) for illuminating a predetermined observation position and having variable illumination conditions is arranged, and a plurality of samples of non-defective products and defective products are sequentially supplied to the observation position, and the non-defective product supplied to the observation position. And each defective sample is imaged under the illumination of the above illumination device, the characteristic amount of each sample is measured based on the video signal obtained by the imaging, and the accuracy of discrimination between the non-defective product and the defective product is based on the measured characteristic amount. A lighting condition setting support method for calculating an evaluation value for each lighting condition while changing the lighting condition of the lighting device and searching for a lighting condition having the best evaluation value. 15. A sample supply device (120, 121) for sequentially supplying a plurality of samples to a predetermined observation position, and an illuminating device (1) having variable illumination conditions for illuminating the sample at the observation position.
0), an image pickup device (20) for picking up an image of each sample brought to the observation position by the supply device under illumination of the lighting device, and outputting a video signal representing the sampled image, output from the image pickup device Feature amount measuring means (130) for measuring the feature amount of each sample based on the video signal
), A means (130) for calculating the variance of the feature quantity measured by the feature quantity measuring means, and the variance is minimized based on the variance for each illumination condition obtained while changing the illumination condition of the illumination device. Means for searching lighting conditions (130
), A lighting condition setting support device. 16. The detection device (123) for detecting a sample supplied to the observation position, further comprising:
The device according to 15. 17. The sample supply device comprises a rotary table (120) on which each sample is placed, and a drive device (121) for rotationally driving the rotary table (120). The described device. 18. An illuminating device (10) having variable illumination conditions for illuminating a predetermined observation position is arranged, a plurality of samples are sequentially supplied to the observation position, and each sample supplied to the observation position is supplied to the illuminating device. Image under the illumination by, the feature amount of each sample is measured based on the image signal obtained by the image pickup, the variance of the feature amount of all the measured samples is calculated, and the illumination condition of the illumination device is changed while the illumination is performed. A lighting condition setting support method that calculates the variance for each condition and searches for the lighting condition with the minimum variance. 19. A camera field-of-view information and camera installation distance information with respect to an object to be photographed in order to determine a photographing condition of a camera in which a lens and a necessary close-up ring are detachable.
An input device for inputting at least two pieces of information of the lens information and the close-up ring information, an arithmetic device for calculating the remaining information using at least two pieces of information input from the input device, and the above arithmetic operation An imaging condition determination assisting device, comprising: a display device for displaying the above remaining information represented by a calculation result by the device.