A Spectral Clustering Image Segmentation Algorithm Based on Nyström Approximation
Abstract
In the image segmentation, the spectral clustering algorithm are facing the problems, that the similarity matrix and Laplace matrix requires a lot of computing and storage, which limits its expansion in the large-scale image. Aiming at these problems, a semi-supervised spectrum clustering algorithm based on the Nyström approximation was proposed. In the algorithm, adopting the Nyström approximation method to estimate the similarity matrix, which effectively reduces the amount of computation and storage of the spectral clustering algorithm. Finally, on the Brodatz texture library, the image segmentation experiments showed the feasibility and effectiveness of the algorithm.
Keywords
Spectral clustering, Nyström approximation, Image segmentation
Publication Date
DOI
10.12783/dtcse/cmsam2016/3596
10.12783/dtcse/cmsam2016/3596
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