Fabric defect detection using Gabor filters and defect classification based on LBP and Tamura method

This paper aims at investigating methods for solving the problem of automated fabric defect detection and classification, which are more essential and important in assuring the fabric quality. The work focuses on two aspects: fabric defect detection and classification. In the experiment, first, the detection texture features for texture defect are extracted using Gabor filters. The method would automatically segment defects from the regular texture. Second, texture features for classification use local binary patterns and Tamura method. Fabric samples are used in evaluation and the experimental results obtained further confirm the designed algorithm achieved a high detection success rate.