计算机技术与发展Issue(12)：32-36,5.DOI:10.3969/j.issn.1673-629X.2014.12.008
基于模糊熵的自适应多阈值图像分割方法
An Adaptive Multi-threshold Image Segmentation Method Based on Fuzzy Entropy
摘要
Abstract
Fuzzy technology,which can well express and deal with uncertain problems,is very important and useful in the field of image processing. Based on the fuzzy theory,an Adaptive Multi-threshold Method (AMM-FE) of image segmentation based on fuzzy entropy is proposed. According to the distribution probability of the image pixels,divide the image into a plurality of regions. Define the member-ship functions using the pixels belonging to the foreground and the background blur in each area,determine the window width of fuzzy membership function by using one-dimension search method,calculating the maximum fuzzy entropy to get the regional optimal thresh-old. By using multi-objective,non-uniform illumination,presence of noise and imperfect image in the experiment,the results show that this method can greatly overcome these incomplete segmentation situations. Compared with traditional single threshold image segmenta-tion methods like Otsu and fuzzy entropy,the effect of this method is significantly improved,which indicates that the proposed AMM-FE method has better adaptability and practicality.关键词
图像分割/模糊熵/隶属度函数窗宽/多阈值图像分割Key words
image segmentation/fuzzy entropy/window width of membership function/multi-threshold image segmentation分类
信息技术与安全科学引用本文复制引用
宋欢欢,李雷..基于模糊熵的自适应多阈值图像分割方法[J].计算机技术与发展,2014,(12):32-36,5.基金项目
国家自然科学基金资助项目(61070234,61071167) （61070234,61071167）
