Fuzzy-Set Based Fast Edge Detection of Medical Image

Yanjun Zeng, C. Tu, Xiaojun Zhang
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引用次数: 8

Abstract

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.
基于模糊集的医学图像快速边缘检测
提出了一种基于模糊子集组合的快速边缘检测方法,将边缘检测作为一个分类问题来考虑,将图像划分为边缘部分和非边缘部分。后者是图像的主要组成部分,由物体和背景组成。从图像中除去非边缘部分,剩下的就是该图像的边缘。本文将灰度直方图划分为若干子区域,并对灰度方差直方图上各子区域的子边缘对应相应的模糊子集进行一些操作,最终得到该图像的边缘。本文的实例表明,所述方法简单有效,可实现医学图像的理想边缘。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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