关键词: 半监督, 超像素, 谱聚类, 模糊隶属度

Abstract: In recent years, spectral clustering algorithm is widely used in the field of image segmentation, and the construction of the similarity matrix is the key of spectral clustering algorithm. Due to the high computational complexity, spectral cluster algorithm is hard to be applied to the large scale image segmentation. Aiming at this problem, a semi-supervised color image segmentation with superpixels and spectral clustering is presented. Firstly, initial partition is performed by the superpixels method. Then the semi-supervised fuzzy similarity measure among the initial partition regions is constructed by utilizing the few label information. Finally, the similarity matrix of the initial partition regions is produced by this similarity measure, and these regions are grouped by normalized cut criterion. Because of the introduction of the label information and fuzzy theory, the experimental results show that the segmentation accuracy and computational complexity of the proposed algorithm paper are improved substantially.

Key words: semi-supervised, superpixels, spectral clustering, fuzzy membership