Super Fuzzy Defect Classifier Based on Self-adaptation

摘要：

Aiming at the situation that feature extraction of image defects is slow, the accuracy is not high, this paper proposes a new super-fuzzy defect classifier based on self-adaptation, in which defect classification can be judged and determined intelligently according to different image windows feature. Firstly, a specific model of adaptive superfuzzy classifier is given. Then, this algorithm is applied to defect recognition of fabric image for algorithm effect checking. Results show that this adaptive super-fuzzy classifier has some characteristics, such as high speed, simple calculation, no membership degree calculation, and the accuracy and threshold of defect classification can be made intelligent estimation according to different cases with this classifier.

关键词： Image defect Self-adaptation Super-fuzzy Classifier

作者: Zhe Liu

作者单位: Zhongyuan University of Technology, Zhengzhou, China

会议类型: 国际会议

会议名称: 2010 International Conference on Advanced Mechanical Engineering(2010年先进机械工程国际学术会议 AME 2010)

会议地点: 洛阳

会议语种:英文

页码: 612-615

在线出版日期: 2010-09-04（万方平台首次上网日期，不代表论文的发表时间）