Research on Digital Image Edge Detection with Local Entropy and Fuzzy Entropy Algorithms

摘要：

A local entropy algorithm and a fuzzy entropy algorithm for image edge detection are proposed respectively in this paper. The precise quantitative relationship between the entropy and the amount of information is utilized in the local entropy algorithm. Because the local window has the filtering characteristics and information extraction characteristics, thus it can be used to process the image with the additive noise without pre-filtering. The fuzzy entropy algorithm gives full consideration to the direction characteristics and the structural characteristics of the edge pixels. Because the gray distribution of neighborhood is orderly and directional, and the gray mutation is structural. Some features are constructed based on fuzzy entropy and then used to detect the image edge. The results of the fuzzy entropy algorithm are compared with that of the local entropy algorithm and other traditional algorithm by adding different noises. The experimental results to various types of images verify the effectiveness of the proposed algorithms and their wide applications.

关键词： Image Edge Detection Fuzzy Entropy algorithm Local Entropy algorithm

作者: Ming Zhao Xiulan Ye Ke Han Yun Li

作者单位: Department of Computer Science and Technology Harbin University of Commerce Harbin,150001,China Beijing Navy 701 FactoryNo.3,Jiuxianqiao Road,Chaoyang District Beijing,100016,China

会议类型: 国际会议

会议名称: 2010 IEEE信息与自动化国际会议(ICIA 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 1-6

在线出版日期: 2010-06-20（万方平台首次上网日期，不代表论文的发表时间）