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Method for detecting and classifying glass defects based on machine vision

A glass defect and machine vision technology, applied in instruments, measuring devices, scientific instruments, etc., can solve the problems that the training samples cannot fully reflect the real situation of the industrial production environment, the algorithm speed is not very satisfactory, etc., and achieve fast computing speed , the algorithm is simple, the effect of high precision

Inactive Publication Date: 2012-01-04
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

Although this method can realize the detection and classification of defects, the training samples are too small to fully reflect the real situation of the industrial production environment, and the speed of the algorithm is not very satisfactory.

Method used

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  • Method for detecting and classifying glass defects based on machine vision
  • Method for detecting and classifying glass defects based on machine vision
  • Method for detecting and classifying glass defects based on machine vision

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Embodiment Construction

[0038] The technical solution of the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. The following examples are implemented on the premise of the technical solutions of the present invention, and detailed implementation methods and processes are given, but the protection scope of the present invention is not limited to the following examples.

[0039] In one embodiment of the present invention, the flow process of the method is as follows figure 1 As shown, the specific implementation steps of this embodiment are as follows (preferably using C++ language programming):

[0040] Step 1: extract the target area in the image, specifically, perform defect edge detection on the image to obtain the edge information of the defect, and determine the target area according to the edge information:

[0041]Since the defect area (considered as the foreground, with a size of approximately 5 pixels*5 pixels) in the i...

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Abstract

The invention relates to a method for detecting and classifying glass defects based on machine vision. The method comprises the following steps of: extracting a defect area in a picture provided by a camera (linear scanning) by Canny edge detection to obtain a minimum connected domain of the defects; processing a target area according to a filter and a W characteristic which are provided by the method; defining nine kinds of characteristic modes, scanning the minimum connected domain according to rows and columns, and counting the emerging frequency of the nine kinds of characteristic modes in a sample; and judging the types of the defects (bubbles are used as hollow defects, and impurities are used as solid defects) on the basis of the emerging frequency. Compared with the prior art, themachine-vision-based method has the advantages of simple algorithm, quick operation speed, high accuracy and the like, and a new reliable method is provided for the detection of the glass defects.

Description

technical field [0001] The invention relates to a method for detecting and classifying glass defects, in particular to a method for detecting and classifying glass defects based on machine vision. Background technique [0002] In industrial production, due to various technical or production process problems, certain defects will be caused. For example, during the glass production process, there will be air bubbles or impurities introduced. Different defects have different effects on product quality. For example, bubble defects may have little effect on ordinary daily glass, but have a great impact on the performance of automotive safety glass. Since May 1, 2003, my country has implemented mandatory inspections for automotive safety glass, architectural safety glass, and railway vehicle safety glass. For products with a large surface area, it is obviously not an efficient method to manually identify defects. In order to avoid losses caused by manual detection misjudgments...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/958
Inventor 赵杰赵旭吴哲孔庆杰刘允才
Owner SHANGHAI JIAO TONG UNIV
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