A Novel Fuzzy Entropy Image Segmentation Approach Based on Grey Relational Analysis
The paper presents a new image segmentation method based on fuzzy entropy function and grey relational analysis. In allusion to the sensitivity towards the noise of the traditional fuzzy entropy method, the grey relational degree is introduced to exactly reflect the degree of the pixels belonging to the object or the background. In the proposed method, the gray values of the current pixel and its neighborhood pixels form a comparative sequence, and then the grey relational degree between the comparative sequence and a reference sequence is computed, based on which the membership function of the fuzzy entropy function is modified. Therefore, the membership of the current pixel is determined not only by its own gray value but also by the gray values of its neighborhood pixels, which help to distinguish the noise from the image more accurately. The segmentation experimental results of the Cameraman and the Tire images show the good performance of the proposed method in reducing the noise.
Ziyang Zhen Zhou Gu Yuanyuan Liu
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 2100 Nanjing Normal University, Nanjing, 210042, P. R. China Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, P. R. China
国际会议
2007年IEEE灰色系统与智能服务国际会议(2007 IEEE International Conference on Grey Systems and Intelligent Services)
南京
英文
2007-11-18（万方平台首次上网日期，不代表论文的发表时间）