KSII Transactions on Internet and Information Systems (TIIS)

  • 제6권4호
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  • Pages.1188-1202
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  • 2012
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  • 1976-7277(pISSN)
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  • 1976-7277(eISSN)
한국인터넷정보학회 (Korean Society for Internet Information)
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A New Connected Coherence Tree Algorithm For Image Segmentation

  • Zhou, Jingbo (The School of Computer Science and Technology, Nanjing University of Science and Technology) ;
  • Gao, Shangbing (The School of Computer Science and Technology, Nanjing University of Science and Technology) ;
  • Jin, Zhong (The School of Computer Science and Technology, Nanjing University of Science and Technology)
  • 투고 : 2011.01.18
  • 심사 : 2012.04.07
  • 발행 : 2012.04.30
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초록

In this paper, we propose a new multi-scale connected coherence tree algorithm (MCCTA) by improving the connected coherence tree algorithm (CCTA). In contrast to many multi-scale image processing algorithms, MCCTA works on multiple scales space of an image and can adaptively change the parameters to capture the coarse and fine level details. Furthermore, we design a Multi-scale Connected Coherence Tree algorithm plus Spectral graph partitioning (MCCTSGP) by combining MCCTA and Spectral graph partitioning in to a new framework. Specifically, the graph nodes are the regions produced by CCTA and the image pixels, and the weights are the affinities between nodes. Then we run a spectral graph partitioning algorithm to partition on the graph which can consider the information both from pixels and regions to improve the quality of segments for providing image segmentation. The experimental results on Berkeley image database demonstrate the accuracy of our algorithm as compared to existing popular methods.

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