Image Segmentation Algorithm based on Improved information Entropy and Grey Relational degree Analysis
The thresholding algorithm based on maximum entropy is an important method of image segmentation. The grey relational degree analysis indicates the correlative degree exactly between two factors. To improve the shortage of the original thresholding method of maximal entropy, some new methods are proposed in this paper. Firstly, parameterize maximal entropy segmentation principle, evaluate the segmentation effect based on Gray-level Contrast and grey relational degree analysis to select parameter.Secondly, introduce the exponential form of entropy and weight it, which reflects gray distribution,select the parameter of weight based on Gray-level Contrast and grey relational degree analysis.Lastly, give a deformation of maximum entropy based on high frequency grayscale, fully considered the effects on segmentation of high frequency grayscale. The experiment results show that threshold value, which is defined by these improved methods of this paper, can get superior segmentation results.
Dianguo Shi Yufeng Gui
School of Sciences, Wuhan University of Technology Wuhan 430063, China
国际会议
2009 IEEE International Conference on Grey System and Intelligent Services(2009 IEEE灰色系统与服务科学国际会议)
南京
英文
62-66
2009-10-20（万方平台首次上网日期，不代表论文的发表时间）