Fuzzy-Set Based Fast Edge Detection of Medical Image

A fast edge detection method basing on the combination of fuzzy subsets is developed, while the detection of an edge as a classification problem will be considered, partitioning the image into two portions: the edge portion and the non-edge portion. The latter one, as the main constituent of an image, consists of the object and its background. Removing the non-edge portion from an image, the remainder is nothing but the edge of this image. In this paper, the gray level histogram is partitioned into several sub-regions, and some operations are performed with the associated fuzzy subsets corresponding to those sub-edges in the sub-regions on the gray-level-square-difference histogram, and the edge of this image is finally obtained. Practical example in this paper illustrates that, the described method is simple and effective to achieve the ideal edge of a medical image.