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期刊论文

Texture Image Segmentation on Improved Watershed and Multiway Spectral Clustering

万旺根Xiuli Ma Wanggen Wan Jincao Yao

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摘要/描述

Spectral clustering is a new graph and similarity based clustering algorithm. When the image is too big, it will take a long time to compute affinity matrix and its eigenvalues and eigenvectors. In order to improve the convergent speed of spectral clustering, a twostage texture segmentation algorithm is proposed in this paper. First, an improved watershed algorithm is used to perform pre-segmentation and then multiway spectral clustering with eigenvalue-scaled eigenvectors performs the final segmentation. This can reduce the runtime greatly and it is valuable to application with high time request. To verify the proposed algorithm, it is applied to texture image segmentation and the segmentation results are satisfying.

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版权说明:以下全部内容由万旺根上传于   2011年05月18日 09时32分54秒,版权归本人所有。

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