Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (10): 182-183.DOI: 10.3778/j.issn.1002-8331.2009.10.055

• 图形、图像、模式识别 • Previous Articles     Next Articles

Image edge detection using new weighted entropy minimal spanning tree algorithm

YANG Fang-fang,CHEN Xiu-hong   

  1. School of Information Engineering,Jiangnan University,Wuxi,Jiangsu 214122,China
  • Received:2008-02-18 Revised:2008-05-05 Online:2009-04-01 Published:2009-04-01
  • Contact: YANG Fang-fang

最小加权熵支撑树图像边缘提取方法

杨方方,陈秀宏   

  1. 江南大学 信息工程学院,江苏 无锡 214122
  • 通讯作者: 杨方方

Abstract: A method of color image edge detection is described.The cluster centers are generated from peaks of the color histogram.After clustering,based on the structure of color image,first,compute the Euclidean distance between neighbor pixels corresponding to the vectors in a specific region,then generate a minimal spanning tree,compute the weighted entropy and study the segmentation threshold based on the pixel vectors in this region,finally,using the vector order statistics method,sorting the gray values and gain the edge result.Experiments show that this method can get satisfied result after processing.

Key words: edge detection, vector order statistics, minimal spanning tree, clustering, weighted entropy

摘要: 提出了一种新的彩色图像边界提取的方法,以色彩图像直方图中搜索到的峰值作为聚类中心,根据彩色图像像素结构的特点,首先计算区域内相邻像素点之间对应的向量的欧式距离,然后构造该区域内的最小支撑树,计算相应的加权熵值确定分割阈值,最后结合向量排序统计,将排序的结果按照灰度值进行分类进行输出,实验证明了这种方法的有效性。

关键词: 边缘检测, 向量排序, 最小支撑树, 聚类, 加权熵