JP2820030B2 - Image display device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention displays a particle or the like to be measured with a density corresponding to a characteristic amount representing a characteristic of the particle such as an area or a shape coefficient, and further uses the specified density as a threshold.
The present invention relates to an image display device that converts an image into a value or a multi-value image and displays the image.

[0002]

2. Description of the Related Art A television camera is connected to a metal microscope to measure nonmetallic inclusions in a steel material to be measured from a captured image. These are JIS-G-05
This method is performed according to the standard 55 or the ASTM standard, and a binary image is created from a captured image, and the size and shape of particles, the number of particles that are continuous within a predetermined interval, and the like are measured to detect nonmetallic inclusions.

[0003]

The sample to be measured is finished in a state where the surface is sufficiently polished by a polishing machine. However, scratches due to the polishing machine may have occurred,
In addition, dust and dirt may adhere, and these are 2
Appears in the value image. Further, even among non-metallic inclusions, there are some that have a small size or the like and do not reach a specified value. For this reason, conventionally, the inspector has to individually determine and discard polishing scratches, dust, and non-metallic inclusions outside the measurement target while viewing the binary image on the screen, but this requires a lot of time and labor. It was hanging.

[0004] In addition, there are cases where it is desired to identify a graphic having a desired size or shape from among various sizes and shapes on a screen. In such a case, an inspector visually checks the screen. Had done these identifications. This was also a time-consuming and labor-intensive task.

The present invention has been made in view of the above-described problems, and provides an image display apparatus which can easily remove unnecessary graphics on a screen or select only necessary graphics. The purpose is to:

[0006]

In order to achieve the above object, an image pickup means for picking up an object to be measured, a binarizing means for binarizing the picked-up image with a predetermined threshold value to obtain a binary image,
A feature value measuring unit that labels the particles displayed in the binary image and measures a feature value representing the feature of each particle; and converts the feature value into a density corresponding to the feature value, and converts the particles representing the feature value into particles. A grayscale image generating means for generating a grayscale image displayed at this density; and
Threshold setting means for setting a threshold for display
And a multi-valued image generating means for converting the value into a binary value or a multi-valued value with the set threshold value.

[0007]

[0008]

[0009]

A binary image is generated by binarizing an image to be measured with a predetermined threshold value, and particles on the binary image (particles include those having a long shape such as a scratch). To label. With respect to the labeled particles, a characteristic amount representing the characteristic of the particle, such as an area or a shape coefficient, is obtained, a density corresponding to the characteristic amount is obtained, and a grayscale image displaying the particle representing the characteristic amount with this density is generated. . The difference in the feature amount is clarified visually by the grayscale image, and the distinction according to the feature amount becomes easy.

Further, while viewing the grayscale image,
Set a threshold to display only
A desired object can be easily identified by binarizing or multi-leveling the value. In particular, since the threshold can be set by the density, the setting is easy, and the identification work is easy. It should be noted that two methods are used to identify particles at a certain concentration or above and below a certain concentration.
Although a value image may be used, ternarization is required in order to distinguish particles in a certain density range from a certain density or lower and a certain other density or higher.

[0011]

[0012]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing the configuration of this embodiment. The microscope 1 is provided with an imaging lens attached to an eyepiece and an imaging device 16 for taking an image through the imaging lens. The position of the stage 17 on which the measurement sample is placed is adjusted by a plane moving mechanism 18 for moving back and forth and left and right by a pulse motor provided on the stand by a signal from the auto stage driver 10, and the vertical moving mechanism 19 is operated by the autofocus driver 11. Then, the stage 17 is moved up and down, and the focus is adjusted.

The A / D converter 2 converts input data from the imaging device 16 from analog to digital, and the input buffer 3 temporarily stores the digital data. The bus 4 transmits signals, the program memory 5 stores a program that defines the operation of the apparatus, and the CPU 6 controls the entire apparatus according to the program.

An image processor 7 performs density processing, binarization processing, image analysis, and the like on the input image data. A density image memory 8 stores density image data.
Stores value or multi-valued image data. The auto stage driver 10 controls the plane moving mechanism 18 to move the stage 17 on which the measurement sample is placed in the X and Y directions in accordance with an instruction from the CPU, and sets the measurement position and area of the measurement sample. The auto-focus driver 11 receives a control command from the CPU 6 to the Z-direction moving mechanism 19, and
9 and focus automatically. Output buffer 1
2 temporarily stores the output data, the D / A converter 13 converts the output data from digital to analog,
The RT 14 displays this output data on the screen. An operator inputs instructions and data from the keyboard 15.

First, the features will be described. As an example of the feature amount, a feature representing a shape is represented by an area, a shape coefficient, or the like. FIG. 2 is a diagram for explaining the shape factor, and FIG. 2A is a diagram for explaining the shape factor of a circle. Assuming that the maximum length of the figure is M and this area is A, the shape factor SF of the circle is expressed by the following equation (1). SF1 = 4A / (πM ² ) (1) Equation (1) becomes 1 in the case of a circle, and becomes smaller as the shape shifts from the circle. (B) is a diagram for explaining the shape factor representing the slenderness ratio. The shape factor SF2 is expressed by the following formula (2) based on the maximum length M and the maximum width B orthogonal thereto. SF 2 = B / M (2) (C) indicates the diameter of the ferrite which is often used to represent the shape, indicates the outer diameter of the object in a certain direction, and FH is the length in the horizontal direction. , FV indicate the length in the vertical direction. The shape factor SF3 is represented by the following equation (3). SF3 = tan ⁻¹ FH / FV (3) Assuming that the image peripheral length is PM, the shape factor SF4 is given by the following (4).
It is expressed by an equation. SF4 = 4πA / PM ² (4)

FIG. 3 is a diagram for explaining a dust coefficient when dust is determined. Dust has various shapes,
As a typical example, there are a fibrous shape that is elongated in one direction, and a shape that is elongated but bent and fits in a rectangle. (A) is a diagram illustrating a dust coefficient DF1 in the case of dust that extends in the horizontal direction. The dust coefficient DF1 is expressed by the following equation (5) based on the area A and the length FH of the dust in the horizontal direction. DF1 = A / FH (5) (B) is a diagram for explaining the dust coefficient DF1 of the dust extending in the vertical direction. The dust coefficient DF1 is expressed by the following equation (6). DF1 = A / FV (6) If DF1 is less than a certain value, it is determined to be dust.

FIG. 3C is a diagram for explaining a dust coefficient DF2 of dust that is bent and is collected in a rectangle. The dust coefficient DF2 is the area of the dust and the horizontal length F
H, and the length FV in the vertical direction is represented by the following equation (7). DF2 = A / (FH · FV) (7) If DF2 is equal to or smaller than a predetermined value, it is determined to be dust.

FIG. 4 is a view for explaining a first display example.
Denotes a binary image obtained by imaging the measurement target and binarized;
(B) shows a gray image in which each particle of the binary image is labeled, the area of the particle is measured, and the particle is represented by a density corresponding to the size of the area. (C) shows a binary image in which a desired density level is set as a threshold value in the grayscale image, and particles having a threshold value or more are extracted by binarization. (D) is a sample of particles below and above the threshold concentration,
An image ternarized by two thresholds, a background threshold and a density threshold, is shown. In the gray scale image of (B), the area of each particle is calculated, and the density is 25 from 25 to 255.
In the case of setting in six levels, the area of each particle is normalized so that the maximum area is about 250, which is slightly smaller than the maximum density of 255, and a value obtained by adding 1 to the normalized value is defined as the density. The reason why 1 is added is to distinguish it from the background (the background density is assumed to be 0). This is not limited to 1 and may be a constant, but the maximum density added should not exceed 255.
In (B), the number of diagonal lines indicates the concentration, and the particles having a larger area have a higher concentration.

In the case of setting a threshold value in the grayscale image (B), it is only necessary to specify a density value serving as the threshold value. Since the density can be easily specified visually, the threshold value is easily set. (A),
The binary image of (C) and the ternary image of (D) have a white background and display particles and figures in colors such as green and red, so that they are easier to see than black and white images.

FIG. 5 is an operation flow chart of the embodiment. First, a measurement object is imaged by a television camera to generate a binary image (S1). It is easier to see the binary image by using a color such as white and green. Next, the particles of the binary image are labeled, a feature amount representing a feature of the particle such as a particle area or a shape coefficient is calculated (S2), and the feature amount is converted into a density. In the conversion, the feature value is normalized in advance so that the feature value does not exceed the maximum value of the density, and the value obtained by adding 1 to the feature value is used as the density. A grayscale image in which each particle is represented by a density corresponding to the characteristic amount is created (S3). The operator sets a threshold value for generating an image displaying only desired particles while viewing the grayscale image, and generates a binary image (S5). When an image within a certain density range is generated, the image is a ternary image. 2 obtained in this way
Measurements such as detection of nonmetallic inclusions in steel are performed by the value (multi-value) image.

FIG. 6 is a diagram for explaining a second display example. This display example shows a case where a shape is identified using a shape coefficient. (A) is an image of a measurement object, which is converted into a binary image. (B) labels each particle of this binary image,
The shape coefficient is obtained, a concentration corresponding to the size of the shape coefficient is obtained, and the corresponding particle is represented by the concentration. The case where the shape factor of the circle shown in the equation (1) is used as the shape factor is shown. As is apparent from equation (1), the shape factor of the circle approaches 1 if it is close to the circle, and the labels 3 and 6 deviate from the circle.
The smaller the value, the smaller the value. In (B), those with many oblique lines are represented as having a high density. (C)
(B) shows an example in which the grayscale image of (B) is a binary image in which the density of an image close to a circle is set as a threshold, and particles having a shape close to a circle are selected and displayed. Since the shape can be identified based on the density as described above, it is possible to easily select a round shape or an elongated shape.

Next, a third display example will be described. In this display example, dust is removed from the image. Particles to be measured, labeled as binary images and measured (5)
Using the equations (6) and (7), the dust coefficients DF1, D
Calculate F2. In the case of DF1, DF × 1 for each particle
A density image with a density of 0 + 1 is created, and in the case of DF2, a density image with a density of DF2 + 1 is created for each particle. When the density of dust to be removed is set as a threshold and a binary image is generated, dust having a density lower than the threshold is removed from the screen. This threshold value can be easily set only by designating the density, so that a binary image with several threshold values can be generated and the best threshold value can be determined.

In the embodiment, an image picked up through a microscope has been described. However, an image picked up directly by an image pick-up means such as a television camera without using a microscope can naturally be applied.
In the above embodiment, the density conversion of the shape coefficient and the area is described as an example. However, for example, the particle density may be assigned to a different density level from the measured density and displayed.

[0024]

As is apparent from the above description, according to the present invention, a feature amount is calculated for particles of a binary image obtained from an object to be measured, and a grayscale image is generated by converting the feature amount into a density. A threshold value of the density is set in the image, and an image obtained by converting the grayscale image into a binary (multi-valued) image using the threshold value is obtained.
The threshold can be easily set, and the particles to be removed can be easily selected.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of an embodiment.

FIG. 2 is a diagram illustrating a shape factor such as a circle.

FIG. 3 is a diagram illustrating a shape factor of dust.

FIG. 4 is a diagram showing a first display example.

FIG. 5 is an operation flowchart of the embodiment.

FIG. 6 is a diagram showing a second display example.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Microscope 5 Program memory 6 CPU 7 Image processor 8 Grayscale image memory 9 Binary memory 14 CRT 15 Keyboard 16 Television camera

Claims (1)

(57) [Claims] An imaging unit for imaging a measurement object, a binarization unit for binarizing an imaged image with a predetermined threshold to obtain a binary image, and labeling particles displayed in the binary image. A feature value measuring means for measuring a feature value representing a feature of each particle, and a grayscale image for converting the feature value into a density corresponding to the feature value and generating a grayscale image displaying the particles representing the feature value at this density Generating means and the desired
Threshold for setting threshold for displaying only particles
An image display device comprising: a value setting unit; and a multi-valued image generation unit that converts a binary value or a multi-valued value with the set threshold value.