关键词: 局部二进制模式, 织物, Tamura纹理特征, 共轭梯度BP算法

Abstract: To find the type of fabric which is easy to produce defects in the production process, and give a feedback to the production process to improve the quality of the fabric, an algorithm based on local binary pattern and Tamura texture features which combined for fabric defect classification is proposed. The main task of the algorithm is to extract feature vectors fabric, local binary pattern describes the texture feature changing from the local, while Tamura texture features method describes the texture feature changing from the global, a good description of defect can be got by combining the two methods. After extracting feature vector, it uses the conjugate gradient BP algorithm to handle the feature vectors. The convergence of conjugate gradient BP algorithm is better, and it improves the training speed and training accuracy. The experimental results show that the proposed algorithm for defect classification has higher accuracy.

Key words: local binary pattern, fabric, Tamura texture features, conjugate gradient BP algorithm