A Novel Fabric Defect Detection Scheme Based on Improved Local Binary Pattern Operator

Local binary pattern (LBP) is one of the features which have been used for texture classification. In this paper, we propose a novel fabric detect detection scheme based on an improve LBP operator. In the training stage, LBP operator is applied on the training sets, and a model is generated according to training using support vector machine (SVM). In the test stage, a test image is divided into the image blocks with size 32×32. LBP features are extracted from the image blocks, the SVM model is used to classify the fabric defects. Experimental results demonstrate the efficiency of our proposed algorithm. Because of its simplicity, online implementation is possible as well.