An Automated Cotton Contamination Detection System Based on Co-occurrence Matriz Contrast Information

摘要：

An automated cotton contamination detection system is economical and efficient to guarantee higher textile quality and lower production cost. A vision system is proposed to realize a fully automated cotton inspection scheme. In the system, cotton contamination is detected based on texture feature. Gray Level Co-occurrence Matrix (GLCM) algorithm is adopted to detect the sharp contrast objects. A rotating search filter based on contextual information is designed to remove the unwanted edges and locate the coordinate of impurities. Experiments using real imagery show that the proposed vision system is suitable to distinguish impurities mixed in cotton.

关键词： Cotton Contamination Detection Gray Level Cooccurrence Matriz tezture feature

作者: Mingxiao Ding Wei Huang Bing Li Shaohong Wu Zhiqiang Wei Yunkuan Wang

作者单位: Institute of Automation Chinese Academy of Sciences Beijing,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 3046-3050

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）