基于中心扰动的区间值模糊集图像阈值分割算法

针对基于区间值模糊集的图像阈值分割问题,提出了一种基于中心扰动的区间值模糊集图像阈值分割算法.采用对目标及背景中心进行扰动的方式,考虑不确定、不精确信息对图像类别中心的影响,并利用限制等价函数构建图像的区间值模糊集模型;在提出一种区间值模糊集上区别度量的基础上建立目标函数来搜索最佳分割阈值.通过对三种类型的图像数据进行仿真实验,结果表明提出的方法在视觉和指标上总体得到了较好的结果,证明了该算法的有效性.

Threshold image segmentation algorithm using interval valued fuzzy set based on central disturbance

To solve the problem of image threshold segmentation based on interval valued fuzzy sets, this paper proposed an threshold image segmentation algorithm using interval valued fuzzy set based on central disturbance. This algorithm used the way of disturbing to the center of object and background in an image, and considered the influence of uncertain and imprecise information on the center of clusters, and constructed interval valued fuzzy set for an image by using restricted equivalence function. Based on the distance measure between interval valued fuzzy sets, the algorithm searched the best segmentation threshold by establishing the objective function. Through the simulation experiment of three types of image data, the results show that the proposed method obtains better results in terms of vision and index, and proves the effectiveness of the algorithm.