JPS6385432A - Inspecting method for linear defect - Google Patents

Abstract

PURPOSE:To inspect a linear defect by removing noises from an input image of a body to be inspected and then calculating the degree of connection between defect cells corresponding to only the linear defect. CONSTITUTION:The image pickup signal of the body 1 to be inspected which is obtained through an image pickup device 3 is stored in an image memory 5 as XY-axial quinary picture element data. Plural cells consisting of plural picture elements as to binary-coded picture element data are set in a matrix in an X and a Y axial direction through a central controller 6. Then, the number of defect picture elements in each cell is calculated. Then, a cell whose number of defect picture elements is larger than a predetermined number is extracted as a defective cell. The degree of connection of those defect cells is calculated. Then, it is decided that cells whose connection degree is larger than a predetermined value are defectives.

Description

DETAILED DESCRIPTION OF THE INVENTION [Industrial Application Field] The present invention relates to a method of inspecting linear defects such as cranks and scratches existing on the surface of electronic parts or precision processed products by image processing.

[Prior Art] ``Conventionally, in order to inspect linear defects such as cranks and scratches that exist on the surface of electronic parts or precision processed products, the object to be inspected is placed within the field of view of a microscope or magnifying glass, and visually inspected. The testing method was the most common method.

However, in the above method, it is difficult to handle particularly small objects to be inspected using pins, etc., and in the case of mass production, the workers become fatigued and it is difficult to continue working for a long time. Furthermore, there are other problems such as inefficiency. In order to solve the above problems, inspection methods using image processing means have been applied in recent years, and many of them are in practical use.

[Problem that the invention seeks to solve]

When the above-mentioned image processing means is applied to the above-mentioned linear defect inspection, there are the following problems. That is, when an image of the object to be inspected is input, unevenness in the background of the object to be inspected is also input as an image and becomes noise, which has the disadvantage that it is impossible to distinguish it from linear defects. Furthermore, when the image signal obtained by imaging the object to be inspected using an imaging means such as a TV camera is binarized using a certain threshold value, the originally continuous image is displayed discontinuously. There is a problem with this. A means for displaying such discontinuous images in a continuous manner is disclosed, for example, in Japanese Patent Application Laid-Open No. 124873/1982. However, such means can detect not only the original linear defects but also the linear defects. There is a risk that noise that exists in the vicinity may be displayed continuously, and non-defective parts may be recognized as defects, resulting in low reproducibility or reliability, and there is a problem that it cannot be applied to actual work. .

The present invention solves the problems existing in the prior art as described above, eliminates noise in input images, and provides highly reliable linear defects that completely inspect linear defects that appear in an apparent continuous earthwork pattern. The purpose is to provide an inspection method for

[Failure to solve the problem]

In order to solve the above-mentioned problems, in the present invention, A.
It is stored in the image memory as valued pixel data.

B. A plurality of cells each consisting of a plurality of pixels are set in a matrix in the X and Y axis directions for the binarized pixel data through the central controller.

The number of defective pixels in each cell of C9 is calculated.

D. Extract cells with a predetermined number or more of defective pixels as defective cells.

E. Compute the connectivity of these defective cells.

F: Those whose degree of connectivity exceeds a predetermined value are determined to be defective.

This technical method was adopted.

[Effect]

With the above configuration, most of the noise in the input image of the object to be inspected is removed at the stage of calculating the number of defective pixels in the cell because the number of pixels in the cell is usually small, so it is noise that is not originally a defect. It has the effect of eliminating the error of recognizing something as a defect.

After eliminating noise as described above, the degree of connectivity between defective cells corresponding only to the linear defect is calculated to inspect the linear defect.

〔Example〕

FIG. 1 is a block diagram of an apparatus in an embodiment of the present invention. In the figure, first, an image of an object to be inspected 1 is imaged through a lens 2 on an imaging device 3 such as a TV camera. Next, the imaging device 3
The AD converter 4 converts the captured image signal into binary pixel data and inputs it into the memory 5. 6 is a processing circuit for processing the contents of the memory 5, and 7 is a memory for storing processing results by the processing circuit.

Next, FIG. 2 (al to (el) are schematic diagrams showing the main parts of the processing procedure of the present invention. First, FIG.
In the figure, binarized pixel data stored in the memory 5 is shown. In the figure, 10 is Tarawak, and inspection object 1
It is a type of linear defect that exists on the surface of. Although the cracks 10 are originally continuous, a portion of the binarized pixel data is discontinuous as shown by 10a.

Reference numeral 11 indicates noise, which is caused by background unevenness on the surface of the object to be inspected 1 and other factors, and is stored as binary pixel data.

Next, in Fig. 2 (bl shows the state in which cells are set. In other words, 12 is a cell, which consists of, for example, 8 x 8 = 64 pixels, and multiple cells are controlled in the X and Y axes directions via a central controller (not shown). Each is set in a matrix. FIG. 2 (bl is an example in which 14 pieces are set on each of the X axis and the Y axis, and 196 pieces in total are set.

FIG. 2 (C1 shows a state in which the number of defective pixels in the cell 12 is calculated. That is, in each cell 12, the number m of defective pixels occupied by the crank 10 and the noise 11 is calculated. If the background has a low density, it will be shown with a high density by the crank 10 and the noise 11, and if the background has a high density, it will be shown with a low density.

FIG. 2 Fdl shows a state in which the defective cell 12a is extracted.

In other words, the number m of defective pixels calculated in FIG. 2(C)
However, a predetermined number of cells above are extracted as defective cells 12a, and cells 12 less than the above number are removed.

The noise 11 that appears as an input image in FIG. By setting , most of the noise can be removed at the stage shown in FIG. 2 fdl, and only the defective cell 12a related to the crank 10 can be extracted.

Therefore, even a defect in a discontinuous state as shown by loa in FIG. 2(al) can be extracted as a defective cell 12a as shown in FIG. 2(d).

FIG. 2(Q) shows a state in which the degree of connectivity is calculated for the defective cell 12a and the crack 10.10a is created as a series of linear defect images 13.

As a result, anything above a predetermined value is determined to be defective, and anything below the above value is accepted and determined to be good.

In this embodiment, an example in which the linear defect of the object to be inspected is a crank has been described, but even if the linear defect is a scratch, a dent, etc., it is possible to display shading on the pixels in the cell. detectable as long as possible. Also, the cell size is 8X
The number should not be limited to 8=64, but should be appropriately selected depending on the type of linear defect to be detected and the noise to be eliminated.

〔Effect of the invention〕

Since the present invention has the structure and operation as described above,
The following effects can be expected.

(1) Since the conventional manual visual inspection can be eliminated, not only can the occupational health environment be dramatically improved, but also productivity can be greatly improved.

(2) Even if the input image signal contains noise other than the original linear defect, it is possible to calculate the number of defective pixels in each cell and extract only the cells above a predetermined number. Therefore, the error is extremely small and the reliability is extremely high.

(3) In the input image signal, even if the defect is discontinuous, linear defects that are originally continuous are recognized and processed as continuous by calculating the degree of connectivity, so reliability and reproducibility are extremely high. expensive.

(4) Not only can the inspection work be automated through the central control device, but also the processing results can be immediately feed-hacked into the production process, which can improve production efficiency and contribute to quality improvement.

[Brief explanation of the drawing]

Fig. 1 is a block diagram of an apparatus in an embodiment of the present invention, and Fig. 2 (al to e) are schematic diagrams showing main parts of the processing procedure of the present invention. 1: Object to be inspected, 5.7 : memory, 6: processing circuit, 10.
10a: crack, 11: noise, 12: cell.

Claims (1)

[Claims] The imaging signal of the object to be inspected obtained through the imaging means is stored in an image memory as binarized pixel data in the XY axis directions, and the binarized pixel data is sent to a cell consisting of a plurality of pixels via a central controller. Set a plurality of cells in a matrix in the X and Y axis directions, calculate the number of defective pixels in each cell, and extract cells with a predetermined number or more of defective pixels as defective cells,
A method for inspecting linear defects, characterized in that the connectivity of these defective cells is calculated, and those whose connectivity is greater than a predetermined value are determined to be defective.