Fabric flaw detection method based on wavelet transformation and genetic algorithm

A genetic algorithm and defect detection technology, applied in computing, image data processing, instruments, etc., can solve the problems of image quality easily affected by industrial environment, fast cloth movement, large cloth size, etc., to achieve fast calculation speed, segmentation Fast, accurate segmentation effects

Inactive Publication Date: 2016-09-07
DONGHUA UNIV
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Problems solved by technology

However, due to the fast movement of the cloth and the large size of the cloth during the detection process, the image quality is easily affected by the industrial environment. Correctly extracting the defective area is called the key and difficult point in the cloth detection

Method used

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  • Fabric flaw detection method based on wavelet transformation and genetic algorithm
  • Fabric flaw detection method based on wavelet transformation and genetic algorithm
  • Fabric flaw detection method based on wavelet transformation and genetic algorithm

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Embodiment Construction

[0033] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0034] Embodiments of the present invention relate to a fabric defect detection method based on wavelet transform and genetic algorithm, such as figure 1 shown, including the following steps:

[0035] (1) Preprocessing the collected images with defects;

[0036] (2) Use wavelet decomposition on the preprocessed image to obtain multi-scale sub-images;

[0037] (3) Fusion the sub-images to obtain the optimal defect edge inform...

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Abstract

The invention relates to a fabric flaw detection method based on wavelet transformation and a genetic algorithm. The method comprises the following steps: preprocessing acquired images with flaws; obtaining multi-dimensional sub-images by performing wavelet decomposition on the preprocessed images; obtaining optimal flaw edge information by performing fusion on the sub-images; calculating a threshold for the sub-images by use of the genetic algorithm, and performing threshold segmentation on the fused images by use of the threshold; and performing morphological processing on the images after threshold segmentation. According to the invention, the cloth flaw segmentation effect after processing is accurate, the segmentation speed is fast, and original forms of the flaws are well reserved.

Description

technical field [0001] The invention relates to the technical field of fabric flaw detection, in particular to a fabric flaw detection method based on wavelet transform and genetic algorithm. Background technique [0002] Fabric defect detection is an indispensable link in the fabric production process, and the manual detection method has been widely used in textile enterprises for a long time. This traditional cloth inspection method is inefficient, the labor intensity of workers is high, and the detection accuracy cannot be guaranteed. It can be seen that the traditional manual inspection method has been difficult to meet the modern management requirements of enterprises. Therefore, the development of a fabric automatic detection equipment has important economic significance for the quality control of textile enterprises and the saving of labor costs. [0003] At present, there are relatively few automatic fabric defect detection systems facing the market, and only a few...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T5/40G06T5/50
CPCG06T7/0004G06T5/40G06T5/50G06T2207/20032G06T2207/20221G06T2207/30124
Inventor 周武能李倩倩
Owner DONGHUA UNIV
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