摘要
针对H.D.Cheng等人提出的模糊熵公式存在不满足区域一致性条件等问题,提出了模糊加权熵公式,证明了该公式满足图像分割定义的五个条件,克服了传统方法导致图像细节被均衡的不足,可得到较佳的分割结果。另外,隶属函数采用一种梯形分布,该分布可降低了参数的维数,提高了运算的效率。
H.D.Cheng introduced fuzziness into maximum entropy approach and proposed the fuzzy e partitions maximum entropy. But it was not satisfied the definition of image segmentation, a fuzzy weighted entropy is proposed to solve the disadvantage. In addition, membership function is a trapezia distribution which can reduce the parameter＇s dimension and shorten the computational time.
出处
《微计算机信息》
北大核心
2006年第12X期308-309,286,共3页
Control & Automation
基金
国家自然科学基金资助项目(60572112)
关键词
图像分割
阈值
模糊熵
隶属函数
Image Segmentation,Threshold,Fuzzy Entropy,Membership Function
