A Novel Spectral Clustering and its Application in Image Processing
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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Eastern Macedonia and Thrace Institute of Technology
2013-01-01
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| Series: | Journal of Engineering Science and Technology Review |
| Subjects: | |
| Online Access: | http://www.jestr.org/downloads/Volume6Issue3/fulltext3632013.pdf |
| Summary: | 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. |
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| ISSN: | 1791-2377 1791-2377 |