DocumentCode
677323
Title
The fabric defect detection technology based on wavelet transform and neural network convergence
Author
Zhiqiang Kang ; Chaohui Yuan ; Qian Yang
Author_Institution
Sch. of Autom., Northwestern Polytech. Univ., Xi´an, China
fYear
2013
fDate
26-28 Aug. 2013
Firstpage
597
Lastpage
601
Abstract
Methods to fabric defects detection are varied, but the common method to detect the fabric defect shapes is slow and poor accuracy. Based on wavelet transform and neural network convergence technologies, this paper presents a new detection method on the fabric defect, which takes full advantage of wavelet transform good time-frequency localization characteristics and multi-scale image analysis capabilities on the fabric defect extraction, neural network technology can against defects for precise identification of the fabric for rapid detection.
Keywords
automatic optical inspection; fabrics; flaw detection; neural nets; production engineering computing; time-frequency analysis; wavelet transforms; detection method; fabric defect detection technology; fabric defect extraction; multiscale image analysis capability; neural network convergence; neural network technology; rapid detection; time-frequency localization characteristics; wavelet transform; Fabrics; Frequency-domain analysis; Gabor filters; Multiresolution analysis; Neural networks; Wavelet transforms; Defect Detection; Neural Network; Rapid detection; Wavelet Transform;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Automation (ICIA), 2013 IEEE International Conference on
Conference_Location
Yinchuan
Type
conf
DOI
10.1109/ICInfA.2013.6720367
Filename
6720367
Link To Document