Tezture Image Segmentation on Improved Watershed and Multiway Spectral Clustering
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 two-stage 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.
Xiuli Ma Wanggen Wan Jincao Yao
School of Communication and Information Engineering, Shanghai University, Shanghai200072, China
国际会议
2008 International Conference on Audio，Language and Image Processing(2008国际声音、语言、图像过程大会)
镇江
英文
1693-1697
2008-07-07（万方平台首次上网日期，不代表论文的发表时间）