DocumentCode :
3159019
Title :
A computer vision approach for fabric defects inspection
Author :
Liu Shu-Guang ; Qu Ping-Ge
Author_Institution :
Xi´an Polytechnic University, 710048 China
fYear :
2009
fDate :
12-14 Oct. 2009
Firstpage :
1
Lastpage :
4
Abstract :
In the textile production, there may appear many fabric defects. To fabric defects, there are a lot of image-based inspection techniques: Fourier transform, Sobel algorithm of edge inspection, fast Fourier transform (FFT) et. However, Wavelet transform is a kind of multiresolution algorithm, and its multiresolution character corresponds to time-frequency multiresolution of human vision. The result of the research indicates that wavelet transform gives better results than the other traditional methods. So in this article, we use wavelet transform and BP neural network together to inspect and classify the fabric defects. A plain white fabric is adopted as the sample, and the distinguishing defects are oil stains, warp-lacking, and weft-lacking. An area camera with 256×256 resolution is used in the scheme, a grabbed image is transmitted to a computer for wavelet transform, and then the corresponding image data are then used in BP neural network as input. The result shows that the fabric defects´ classification rate can be up to 95% with above method.
Keywords :
computer vision; fabric defect; inspection; wavelet transform;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Technology and Innovation Conference 2009 (ITIC 2009), International
Conference_Location :
Xian, China
Type :
conf
DOI :
10.1049/cp.2009.1521
Filename :
5518602
Link To Document :
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