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  • 曹俊杰 ( 副教授 )

    的个人主页 http://faculty.dlut.edu.cn/jjcao/en/index.htm

  •   副教授   硕士生导师
论文成果 当前位置: jjcao >> 科学研究 >> 论文成果
Fabric defects detection using adaptive wavelets

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论文类型:期刊论文
发表时间:2014-05-27
发表刊物:INTERNATIONAL JOURNAL OF CLOTHING SCIENCE AND TECHNOLOGY
收录刊物:SCIE、EI
卷号:26
期号:3
页面范围:202-211
ISSN号:0955-6222
关键字:Textile industry; Fabric; Adaptive wavelets; Fabric defects detection; Wavelet filter coefficients
摘要:Purpose - Fabric defects detection is vital in the automation of textile industry. The purpose of this paper is to develop and implement a new fabric defects detection method based on adaptive wavelet.
   Design/methodology/approach - Fabric defects can be regarded as the abrupt features of textile images with uniform background textures. Wavelets have compact support and can represent these textures. When there is an abrupt feature existed, the response is totally different with the response of the background textures, so wavelets can detect these abrupt features. This method designs the appropriate wavelet bases for different fabric images adaptively. The defects can be detected accurately.
   Findings - The proposed method achieves accurate detection of fabric defects. The experimental results suggest that the approach is effective.
   Originality/value - This paper develops an appropriate method to design wavelet filter coefficients for detecting fabric defects, which is called adaptive wavelet. And it is helpful to realize the automation of textile industry.

 

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