A Novel Segmentation Method Using Improved PCNN for Fabric Defect Image

摘要：

Fabric defect image segmentation is not only a key stage on real-time visual detection but also a very difficult problem. A novel method for fabric defect image segmentation using improved Pulse Couple Neural Networks (PCNN) is proposed. According to diiTerent gray intensity between the field of defects and the field of no defects, PCNN neuron cell is fired to im plement segmentation. The iteration index of PCNN is controlled by the minimum cross entropy. And, segmenta tion evaluation criteria is also presented in this paper. The validity tests on the developed algorithms have been performed with some fabric defect images. Experimental results show that the proposed method can segment common fabric defect quickly and correctly. It is more efTective than other methods using performance evaluation.

关键词： Pulse Coupled Neural Networks (PCNN) image segmentation fabric defects evaluation criteria

作者: Xiaojun Jia

作者单位: College of Mathematics and Information Engineering, Jiaxing University Jiaxing, China,314001

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)

会议地点: 大连

会议语种:英文

页码: 388-392

在线出版日期: 2010-07-05（万方平台首次上网日期，不代表论文的发表时间）