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A new image segmentation algorithm: A community detection approach

Abin, A. A ; Sharif University of Technology | 2011

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  1. Type of Document: Article
  2. Publisher: 2011
  3. Abstract:
  4. The goal of image segmentation is to find regions that represent objects or meaningful parts of objects. In this paper a new method is presented for color image segmentation which involves the ideas used for community detection in social networks. In the proposed method an initial segmentation is applied to partition input image into small homogeneous regions. Then a weighted network is constructed from the regions, and a community detection algorithm is applied to it. The detected communities represent segments of the image. A remarkable feature of the method is the ability to segments the image automatically by optimizing the modularity value in the constructed network. The performance of the proposed algorithm is evaluated on Berkeley Segmentation Database and compared with some well known methods. The results show that the proposed algorithm performs better than the other known algorithms in terms of qualitative accuracy. The proposed algorithm being simple and easy to implement, is well suited for fast processing applications
  5. Keywords:
  6. Berkeley Segmentation Database ; Color image segmentation ; Color images ; Community detection ; Community detection algorithms ; Community structures ; Complex networks ; Constructed networks ; Homogeneous regions ; Image segmentation algorithm ; Initial segmentation ; Input image ; Processing applications ; Social Networks ; Weighted networks ; Algorithms ; Artificial intelligence ; Population dynamics ; Image segmentation
  7. Source: Proceedings of the 5th Indian International Conference on Artificial Intelligence, IICAI 2011, 14 December 2011 through 16 December 2011 ; December , 2011 , Pages 1047-1059 ; 9780972741286 (ISBN)