Fabric Defect Detection Based on Adaptive Local Binary Patterns

摘要：

Adaptive local binary patterns method is proposed in this paper, on which an effective fabric defect detection algorithm is designed. ALBP method selects the frequently occurred patterns to construct the main pattern set, which avoids using the same pattern set to describe different texture structures in uniform local binary patterns method. The features of free defect image are extracted according to the set and the threshold is confirmed. The image to be tested is divided into same size detection windows from which ALBP features are also extracted. Defective window is found through comparing ALBP features with threshold. The experiment exhibited the detection effect of the proposed method is comparatively better than traditional LBP method from human visual aspect and detection accuracy.

作者: Rong Fu Meihong Shi Hongli Wei Huijuan Chen

作者单位: School of Computer Science,Xian Polytechnic University School of Electronic Engineering,Xidian Univ School of Computer Science,Xian Polytechnic University,Xian China School of Electronic Information Engineering,Xian Technological University,Xian China School of Computer Science,Xian Polytechnic University

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)

会议地点: 桂林

会议语种:英文

页码: 1336-1340

在线出版日期: 2009-12-19（万方平台首次上网日期，不代表论文的发表时间）