Abstract:

Owing to its low contrast, the defects of fabric images for background texture saliency are not very salient, and they are difficult to detect automatically. Aimed at this problem, a method for fabric defects detection based on texture saliency features is proposed in the paper. Firstly, in view of robustness of Tamura texture features, good discrimination and rotation invariance to texture, we present an improved local texture coarseness algorithm(ILTCA) based on multi-scale calculation in order to further enhance discrimination to local texture. Then on a fabric image, coarseness, contrast and direction are calculated respectively based on optimal scale of local textures in accordance with ILTCA and three characteristic sub-maps are obtained, a salient feature map is formed by normalization and weighted fusion for difference sub-maps. Finally, comparing with the existing methods of fabric defects detection based on visional saliency feature, the comparing experiment results on the TILDA texture databases show that the proposed method can effectively isolate fabric defects from salient background texture and fabric defects detected has good homogeneity and integrality.

Key words: texture saliency, local texture, multi-scale calculation, fabric defect detection