A Novel Spectral Clustering and its Application in Image Processing

• Main Authors: Gu Ruijun, Chen Shenglei, Wang Jiacai
• Format: Article
• Language: English
• Published: Eastern Macedonia and Thrace Institute of Technology 2013-01-01
• Series: Journal of Engineering Science and Technology Review
• Subjects: Spectral graph theory; Spectral clustering; Neighbour adaptive scale; Image segmentation
• Online Access: http://www.jestr.org/downloads/Volume6Issue3/fulltext3632013.pdf

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.