计算机工程与应用Issue(21)：184-188,5.DOI:10.3778/j.issn.1002-8331.1311-0473
基于改进谱聚类的图像分割算法
Image segmentation based on improved spectral clustering algorithm
关昕 1周积林2
作者信息
- 1. 辽宁工程技术大学 电子与信息工程学院，辽宁 葫芦岛 125105
- 2. 辽宁工程技术大学 研究生学院，辽宁 葫芦岛 125105
- 折叠
摘要
Abstract
Aiming at the default that when the traditional spectral clustering algorithm is applied to image segmentation, it only uses the feature similarity information to construct similarity matrix and ignores the spatial adjacency information defect of spatial distribution of pixels, this paper presents a new similarity measure formula—weighted euclidean distance of the Gaussian kernel function, making full use of image feature similarity information and spatial adjacency information to structure similarity matrix. In the spectral mapping process, using Nystrom approximation strategy to approximate simi-larity matrix and eigenvectors, it greatly reduces the computational complexity to solve similarity matrix and reduces the memory consumption. This paper applies a new clustering algorithm—Affinity Propagation to the low-dimensional sub-space. It avoids the defect that traditional spectral clustering using K-means algorithm can not automatically determine the number of clusters and it is sensitive to initial value and easy to fall into local optimum. The experiments prove that the proposed algorithm obtains better segmentation results than the traditional spectral clustering algorithm.关键词
谱聚类/空间临近信息/相似性矩阵/Nystrom逼近策略/近邻传播聚类算法Key words
spectral clustering/spatial adjacency information/similarity matrix/Nystrom approximation/Affinity Propa-gation(AP)algorithm分类
信息技术与安全科学引用本文复制引用
关昕,周积林..基于改进谱聚类的图像分割算法[J].计算机工程与应用,2014,(21):184-188,5.
