个人信息Personal Information
教授
博士生导师
硕士生导师
性别:女
毕业院校:大连理工大学
学位:博士
所在单位:数学科学学院
电子邮箱:xpliu@dlut.edu.cn
Fabric defects detection using adaptive wavelets
点击次数:
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.