医学图像边缘快速检测的模糊集方法

为了简单有效地获得理想的医学图像边缘,进行医学诊断,提出了一种基于模糊子集组合的图像边缘检测方法.由于图像边缘的模糊性,在边缘检测过程中应用了模糊集运算方法:先将图像的灰度直方图划分成相应的几个不同的子区,并对与灰度方差直方图子区相应的模糊子集进行运算,综合运算结果,最终得到图像的边缘.文中实例及对几种方法的比较表明,提出的Fuzzy算子所得到的图像边缘优于Sobel算子和Prewitt算子时所得到的图像边缘.

Fuzzy-set Method for Fast Edge Detection of Medical Image

In order to achieve simply and effectively the ideal edge of a medical image and thus perform an effective medical diagnose, a fast edge detection method based on the combination of fuzzy subsets is developed. We partition an image into two portions: the edge portion and the non-edge portion. Non-edge portion, consisting of the objects and its background, is removed from an image; the remainder is image's edge. Considering the fuzziness of image's edge, some fuzzy operations can be carried out. We firstly partition the gray-level histogram into several sub-regions and operate corresponding fuzzy subsets. Finally, image's edge is obtained. Experiment results show as compared with Sobel operator or Prewitt operator, that the described method is more excellent.