A method of cloth defect detection based on visual saliency

A defect detection and salience technology, which is applied in image data processing, instruments, calculations, etc., can solve problems such as poor direction selectivity, inaccurate positioning, and increased computational complexity, so as to reduce complexity, improve recognition rate, and reduce interference. Effect

Active Publication Date: 2017-02-01
SUZHOU UNIV
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Problems solved by technology

The Fourier transform is a global transformation of the image, so it cannot accurately locate the defect; the transformation detection performance of the Gabor analysis is better, but it needs to perform two-dimensional filtering and fusion on the multi-channel direction, which greatly increases the computational complexity; the wavelet transform has a good Local time-frequency analysis, fast calculation speed, etc., but the poor direction selectivity makes it unable to describe the characteristics of the two-dimensional graph well, resulting in unsatisfactory detection results

Method used

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  • A method of cloth defect detection based on visual saliency
  • A method of cloth defect detection based on visual saliency
  • A method of cloth defect detection based on visual saliency

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Embodiment

[0030] Example: see figure 1 , as shown in the legend, the above cloth defect detection method includes the following steps:

[0031] (1) Collect images, collect images of cloth through industrial cameras, and obtain initial grayscale images ,Such as figure 2 (a) is the initial image of the cloth intact image, such as image 3 (a) is the initial grayscale image of a typical cloth defect image.

[0032] (2), Brightness feature processing:

[0033] a. The above initial grayscale image input through a two-dimensional Gaussian filter Perform Gaussian pyramid filtering. Pyramid filtering refers to continuous 1 / 2 downsampling and filtering of the initial grayscale image. The scale factor of the filter decreases as the image decreases, and a set of filtering results at different scales is obtained. In this example The pyramid level is 2, that is, the filtering results of different brightness features at two scales are obtained, that is, two brightness feature maps ;

[003...

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Abstract

The invention discloses a cloth defect detection method based on visual salience, which comprises the following steps: (1) collecting images; (2) processing brightness features; (3) processing direction features; (4) multi-channel superposition and normalizing processing; (5) Grayscale image processing; (6) Binarization processing; (7) Defect area judgment. Compared with the traditional cloth defect detection method, the present invention reduces the complexity of calculation, improves the recognition rate, and can accurately locate , and at the same time, it avoids false detections easily caused by the case where the gray value of the salient image of the detected cloth intact image is higher than the gray value of the intact part of the defect image, effectively reducing the interference of the background during the detection process, and reducing It prevents the misjudgment of the target area obtained by the adaptive threshold segmentation of the image of the intact cloth as the defective area.

Description

technical field [0001] The invention relates to a cloth defect detection method, in particular to a cloth defect detection method based on visual salience. Background technique [0002] In modern textile production, quality control and testing are very important, and cloth defect detection is a particularly critical component. At present, domestic textile enterprises mainly use manual testing methods, and the detection speed of human eyes is limited, and the detection results are easily affected. Influenced by subjective factors, false detection and missed detection are prone to occur. Replacing manual cloth defect detection with advanced automatic detection technology is an important measure to improve detection efficiency, reduce labor, reduce labor intensity and ensure cloth quality. Scholars at home and abroad have made many outstanding achievements in the research of automatic detection methods. [0003] The cloth defect detection algorithm mainly judges the defect ac...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00
Inventor 何志勇孙立宁胡佳娟翁桂荣左保齐余雷
Owner SUZHOU UNIV
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