摘要
目的本文提出一种新颖的基于模糊同质直方图和数据融合技术的彩色图像分割算法。方法首先计算图像的同质特征和同质直方图,然后检测出直方图的峰值点对RGB彩色图像各层进行初始分割,最后计算各基色彩色图像的概率分配函数,使用基于正交和的Dempster-Shafer(DS)理论合并规则进行图像融合,得到最终的彩色分割图像。结果选用人工合成和多种医学图像进行仿真实验。定性分析表明基于本文算法的分割图像对比度和清晰度均最优,且图像中细胞边界清晰完整,细胞数量真实可靠;定量评估结果显示基于本文算法的图像分割敏感度均最高,显著优于现存的基于目标点到原型成员之间距离的优良模型(Model for Membership Functions,MMFD)和高斯分布假设和直方图阈值(Model Mass Function Method Based on the Assumption of Gaussian Distribution,MMFAGD)算法,且基于同质直方图优于FCM(Fuzzy C-Means)和HCM(Hard C-Means)产生的概率分配函数。结论基于模糊同质直方图的DS证据理论是一种可行的彩色图像分割算法,不仅能获得优质、稳定、准确的彩色分割图像,而且优越于其他现存的分割算法。
Objective This paper presents a novel method of color image segmentation based on fuzzy homogeneity and data fusion techniques.Methods The general idea of mass function estimation in the Dempster-Shafer(DS)evidence theory of the histogram was extended to the homogeneity domain.Firstly the fuzzy homogeneity vector was used to determine the fuzzy region in each primitive color,then,the evidence theory was employed to merge different data sources in order to increase the quality of the information and to obtain an optimal segmented image.Results Both simulated and clinical datasets were evaluated by different methods.Qualitative analysis showed that the proposed method,which used both local and global information for mass function calculation in DS evidence theory,was more accurate than the traditional methods in terms of segmentation quality.Quantitative evaluation results showed that the proposed method could achieved higher segmentation sensitivity values than HCM and FCM.Conclusion The experimental results demonstrate the superiority of introducing the fuzzy homogeneity method in evidence theory for image segmentation.
作者
陆小妍
周啸虎
张子齐
LU Xiaoyan;ZHOU Xiaohu;ZHANG Ziqi(Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing Jiangsu 210006, China)
出处
《中国医疗设备》
2018年第1期61-64,68,共5页
China Medical Devices
基金
国家自然科学基金(81601477)
关键词
模糊同质方法
数据融合
图像分割
概率分布函数
DS证据理论
峰值点检测算法
fuzzy homogeneity method
data fusion
image segmentation
probability distribution function
Dempster-Shafer evidence theory
peak finding method
