河北工业科技2018，Vol.35Issue(1)：55-60,6.DOI:10.7535/hbgykj.2018yx01010
基于改进谱聚类算法在图像分割中的应用
Application of improved spectral clustering algorithm in image segmentation
摘要
Abstract
To solve the problem of large usage of the similar matrix memory,even overflowing,and the large amount of calcu-lation when spectral clustering algorithm is applied in image segmentation,a part of sample points are obtained by using the Nystrom method,according to the two similarity relations between sample points and sample points,sample points and non-sample points to get the similarity relation of all pixel points,then the approximate similarity matrix of the original image is got.In building the two block similar matrixs required in Nystrom,cosine function is used to overcome the absoluteness of Euclidean distance in the distance measurement.In this paper,the nearest neighbor propagation clustering algorithm is used to replace the k-means algorithm to overcome the sensitivity to the initial value in the clustering process,thus obtaining a more stable effect.The experimental results of the 4 real images show that the method is far superior,and the improved spectral clustering algorithm provides reference for the stable study of image segmentation.关键词
图像处理/图像分割/谱聚类/Nystrom方法/余弦距离/AP算法Key words
image processing/image segmentation/spectral clustering/Nystrom method/cosine distance/AP algorithm分类
信息技术与安全科学引用本文复制引用
王贝贝,杨明,燕慧超..基于改进谱聚类算法在图像分割中的应用[J].河北工业科技,2018,35(1):55-60,6.基金项目
国家自然科学基金(61601412,61571404,61471325) （61601412,61571404,61471325）
山西省自然科学基金(2015021099) （2015021099）
