Pacific-Asia Workshop on Computational Intelligence and Industrial Application, IEEE (2008)
Dec. 19, 2008 to Dec. 20, 2008
On the basis of wavelet and singular signal characteristic analysis, a new defect detection method based on wavelet characteristics is presented. Firstly, to select wavelet filters of compact support and high vanishing moment properties are regarded as finite biorthogonal filters. Secondly, the new wavelet with concussive and filters coefficients of centralized distribution is constructed by lifting scheme, which is matching with test fabric texture properties. Lastly, the detail signal feature after wavelet decomposition of fabric image is extracted, and it is compared with the detail signal feature of normal fabric image decomposition to determine whether there exists defect. The experimental result confirms that the proposed method is validity and the detection accuracy is over 92.5%.
Wavelet characteristics, Lifting Sheme, Feature extraction, Defect Detection
H. Cui, X. Shi, Y. Song and S. Guan, "Fabric Defect Detection Based on Wavelet Characteristics," 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application. PACIIA 2008(PACIIA), Wuhan, 2008, pp. 366-370.