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 :
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