Part Recognition Based on Mazimum Mutual Information

摘要：

A new approach to the problem of part recognition is proposed by using maximum mutual information. The method applies entropy to measure image feature, combined with color information and local shape information, and uses mutual information as a new matching criterion between the images for image recognition. This method solves the problem that histogram algorithm can not represent the spatial information. This method not only has the feature of translation invariant, but also avoids image segmentation which may lead to a complex calculation, so it can be realized easily. The result shows that proposed approach is accuracy, stability, and reliability in the processing of machine part image recognition.

关键词： entropy image recognition mutual information machine part image

作者: GE Sen HUANG Dagui

作者单位: School of Mechatronics Engineering University of Electronic Science and Technology of China, Chengdu School of Mechatronics Engineering University of Electronic Science and Technology of China,Chengdu,

会议类型: 国际会议

会议名称: 第九届加工技术进展国际会议(9th International Conference on Progress of Machining Technology)

会议地点: 昆明

会议语种:英文

页码: 234-238

在线出版日期: 2009-04-25（万方平台首次上网日期，不代表论文的发表时间）