A novel spectral clustering and its application in image processing

被引：0
作者：
机构：
[1] School of Information Science, Nanjing Audit University, Nanjing
来源：
Ruijun, G. (grj79@hotmail.com) | 1600年 / International Hellenic University - School of Science卷 / 06期
关键词：
Image segmentation; Neighbour adaptive scale; Spectral clustering; Spectral graph theory;
D O I：
10.25103/jestr.063.03
中图分类号：
学科分类号：
摘要：
This paper proposes an improved spectral clustering algorithm based on neighbour adaptive scale, who fully considers the local structure of dataset using neighbour adaptive scale, which simplifies the selection of parameters and makes the improved algorithm insensitive to both density and outliers. This paper illustrates the proposed algorithm not only has inhibition for certain outliers but is able to cluster the data sets with different scales. Experiments on UCI data sets show that the proposed method is effective. Some experiments were also performed in image clustering and image segmentation to demonstrate its excellent features in application. © 2013 Kavala Institute of Technology.
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页码：10 / 15
页数：5
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