JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2016, Vol. 46 ›› Issue (1): 28-33.doi: 10.6040/j.issn.1672-3961.1.2015.030

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An improved multi-scale Graph cut algorithm

FAN Shuyan1,2, DING Shifei1,2*   

  1. 1. School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China;
    2. Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Science, Beijing 100190, China
  • Received:2015-05-12 Online:2016-02-20 Published:2015-05-12

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Abstract: Aimed at Graph cut algorithm that has the short comings of high computational and possible aver-segmentation, a developed algorithm was presented. The algorithm used multi-scale normalized cut as an objective function of Graph cut algorithm which could avoid the over-segmentation phenomenon. Meanwhile, by combining accuracy of fine scale and easy divisibility of rough scale, sampling pixels not only retained the relationship between the original pixels, but also reduced computational complexity. By using the solving approach based on spectral graph theory, the problem was transformed into similarity matrix eigenvalue and eigenvectors problems, and the similarity was high. Experimental results showed that the proposed algorithm could effectively segment images without user interaction. The segmentation process was fast and segmentation results were accurate.

Key words: spectral clustering, graph theory, image segmentation, multi-scale, graph cut, Normalized cut

CLC Number: 

  • TP18
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