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Method and device for rapidly detecting and classifying defects of glass image

A defect detection and classification method technology, applied in image analysis, image data processing, instruments, etc., can solve problems such as difficult defect detection and classification tasks

Active Publication Date: 2011-03-30
INST OF COMPUTING TECH CHINESE ACAD OF SCI
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Problems solved by technology

But in fact, the influence of these factors will make the task of defect detection and classification very difficult, that is, to judge whether there is a defect in a certain area of ​​the input image, and whether the defect belongs to a predefined defect category or an undefined defect category

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  • Method and device for rapidly detecting and classifying defects of glass image
  • Method and device for rapidly detecting and classifying defects of glass image
  • Method and device for rapidly detecting and classifying defects of glass image

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Embodiment Construction

[0152] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments, but not as a limitation of the present invention.

[0153] Such as figure 1 The above is a flow chart of the fast glass image defect detection and classification method of the present invention. The method is a fast and robust defect detection and classification method suitable for glass original sheets containing noise. The method can be divided into two Stages: The first is the defect domain detection stage; the second is the defect classification stage. Specifically include the following steps:

[0154] Step 101, for the input glass image frame, adopt the method of window scanning, according to the measure of the balance of the gray scale distribution in the window, obtain the candidate window (candidate defect window) that may contain defects;

[0155] Step 102, according to the positional relationship of the candidate defect windows, the...

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Abstract

The invention relates to a method and device for rapidly detecting and classifying defects of a glass image, wherein the method comprises the steps of: 1, scanning windows of an input glass image, measuring according to the balance of gray level distribution in the windows to obtain candidate defect windows; 2, merging the adjacent candidate defect windows according to the position relationship of the candidate defect windows to obtain a candidate defect region; 3, obtaining background information of the candidate defect region, and extracting a defect domain according to the gray level distribution mode of the candidate defect region; and 4, normalizing the defect domain according to the scale, extracting characteristic vectors, and classifying the defects according to the characteristic vectors to obtain a defect classifying result. By adopting the method, the defects in a glass image frame containing the noise can be accurately detected, the class of the defects can be effectively distinguished and the undefined defects can be judged.

Description

technical field [0001] The invention relates to the technical fields of image processing, computer vision and pattern recognition, in particular to a fast glass image defect detection and classification method and a device thereof. Background technique [0002] The traditional detection and classification of glass image defects is done manually, but this method is affected by human subjective factors, has low efficiency, and is difficult to meet the needs of continuous development of production. With the continuous development of computing technology, the use of digital image processing technology to analyze images to detect defects has gradually become the mainstream in the field of industrial defect detection. This technology has the advantages of fast detection speed and no manual operation, and has broad application prospects. However, the change of lighting conditions, the complexity of defect formation, and the influence of various suspended substances on the glass (s...

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Application Information

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IPC IPC(8): G06T7/00G06K9/62
Inventor 陈熙霖柴秀娟崔振武斌郑媛陈海峰
Owner INST OF COMPUTING TECH CHINESE ACAD OF SCI
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