A stainless steel surface defect detection method based on machine vision

A defect detection and machine vision technology, applied in the field of iron and steel manufacturing, can solve problems such as difficulty in detection and the influence of subjective factors of inspection personnel in inspection results, and achieve the effect of high inspection efficiency and accurate inspection results.

Inactive Publication Date: 2017-12-15
GUANGDONG UNIV OF TECH
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Problems solved by technology

However, this method has many shortcomings, such as: 1. The test results are easily affected by the subjective factors of the testers;

Method used

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  • A stainless steel surface defect detection method based on machine vision
  • A stainless steel surface defect detection method based on machine vision
  • A stainless steel surface defect detection method based on machine vision

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Embodiment Construction

[0071] The present invention will be further described below in conjunction with specific embodiment:

[0072] See attached Figure 1-2 As shown, the machine vision-based stainless steel surface defect detection method described in this embodiment includes the following steps:

[0073] S1. Use a CCD industrial camera to collect the surface image of the stainless steel to be detected;

[0074] S2. Perform two-dimensional defect detection based on Blob analysis on the collected stainless steel surface image to be detected, the steps are as follows:

[0075] S21. Select ROI area:

[0076] The global threshold method is used to segment the ROI area, that is, the stainless steel plate area, and then the connected domain of the stainless steel plate is extracted. Suppose the image to be segmented is f(x, y), and the image after threshold segmentation is S(x, y), then

[0077]

[0078] Among them, T is the segmentation threshold;

[0079] S22. Image preprocessing:

[0080] Per...

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Abstract

The invention relates to a stainless steel surface defect detection method based on machine vision. The method includes S1) collecting a surface image of stainless steel to be detected by adopting a CCD industrial camera; S2) subjecting the collected surface image of the stainless steel to be detected to two-dimensional defect detection based on Blob analysis; S3) subjecting the collected surface image of the stainless steel to be detected to three-dimensional defect detection according to frequency-domain-based Fourier transform; and S4) separating out the defective stainless steel according to two-dimensional and three-dimensional defect detection results. For two-dimensional defects, a surface detect detection algorithm based on the Blob analysis is provided, and a frequency-domain-based Fourier transform algorithm is provided for three-dimensional defects. Common surface defects, such as scratch, oil stain, rust, air bubbles, cracks, impurities, rolling marks and roll marks, of stainless steel products can be effectively detected. In addition, the detection results of a scheme are accurate and the detection efficiency is high.

Description

technical field [0001] The invention relates to the technical field of iron and steel manufacturing, in particular to a machine vision-based detection method for stainless steel surface defects. Background technique [0002] The production and manufacture of steel is a very important factor affecting the national economy and industrial modernization of a country. For example, in daily life, stainless steel products are used in various aspects. Therefore, the quality inspection of stainless steel is particularly important. [0003] Stainless steel surface defects are usually divided into two-dimensional defects and three-dimensional defects. The surface defect detection of traditional stainless steel is completed by inspectors through human eyes. However, this method has many shortcomings, such as: 1. The test results are easily affected by the subjective factors of the testers; 2. It can only be used to detect the stainless steel surface with a slow running speed; 3. It i...

Claims

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Application Information

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IPC IPC(8): G01N21/88
CPCG01N21/8851G01N2021/8887
Inventor 张美杰张平张乐宇
Owner GUANGDONG UNIV OF TECH
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