计算机工程与应用2011，Vol.47Issue(16)：172-175,4.DOI:10.3778/j.issn.1002-8331.2011.16.052
模糊Renyi熵与QGA结合的快速图像分割
Fast image segmentation based on fuzzy Renyi entropy and quantum genetic algorithm
摘要
Abstract
Digital image are by nature fuzzy,while traditional threshold method doesn't reflect this fact. In order to retain the fuzziness of image,a new image threshold method based on fuzzy entropy is presented. Transforming the histogram of image into fuzzy domain by fuzzy membership function, the entropy of objects and background is calculated according to the definition of fuzzy Renyi Entropy. Following the maximum entropy principle,Quantum Genetic Algorithm(QGA) is employed to accelerate the search of the optimal parameters of membership function, and thus the best threshold of image is obtained by the combination of these parameters. The experimental results indicate that the proposed method obtains good performance,and satisfies the requirement of real-time.关键词
图像分割/模糊Renyi熵/量子遗传算法/最大熵原则Key words
image segmentation/fuzzy Renyi entropy/quantum genetic algorithm/maximum entropy principle分类
信息技术与安全科学引用本文复制引用
赵敏,张路,孙棣华,阳树洪..模糊Renyi熵与QGA结合的快速图像分割[J].计算机工程与应用,2011,47(16):172-175,4.基金项目
国家高技术研究发展计划(863)(the National High-Tech Research and Development Plan of China under Gram No.2006AA04A124) （863）
教育部博士点专项基金(No.20090191110022). （No.20090191110022）
