Fabric defect detection based on textured characteristics using wavelet transform

Ziguang Sun; Zhiqi Liu; Xiaorong Wang; YiYi Xu

doi:10.1117/12.867457

19 August 2010 Fabric defect detection based on textured characteristics using wavelet transform

Ziguang Sun, Zhiqi Liu, Xiaorong Wang, YiYi Xu

Proceedings Volume 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering; 78200F (2010) https://doi.org/10.1117/12.867457
Event: International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 2010, Xi'an, China

Abstract

In texture defect detection, the defects can be discriminated according to the distribution ranges of wavelet coefficients between the normal and defective parts of texture images. In traditional texture defect detection methods, the normal parts of texture images have to be trained in advance. In this paper, we propose a novel method to automatically determine the training regions based on the characteristics exhibited by normal and defective texture images. In this way, the detection error can be reduced because of the avoiding of environmental changes.

Citation Download Citation

Ziguang Sun, Zhiqi Liu, Xiaorong Wang, and YiYi Xu "Fabric defect detection based on textured characteristics using wavelet transform", Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 78200F (19 August 2010); https://doi.org/10.1117/12.867457

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KEYWORDS

Wavelet transforms

Defect detection

Feature extraction

Wavelets

Wavelet packet decomposition

Image filtering

Image processing

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