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A Phase-Field Based Segmentation Algorithm for Jacquard Images Using Multi-start Fuzzy Optimization Strategy

  • Zhilin Feng
  • Jianwei Yin
  • Hui Zhang
  • Jinxiang Dong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3614)

Abstract

Phase field model has been well acknowledged as an important method for image segmentation. This paper discussed the problem of jacquard image segmentation by approaching the phase field paradigm from a numerical approximation perspective. For fuzzy theory provides flexible and efficient techniques for dealing with conflicting optimization probelms, a novel fuzzy optimization algorithm for numerical solving of the model was proposed. To achieve global minimum of the model, a multi-start fuzzy strategy which combined a local minimization procedure with genetic algorithm was enforced. As the local minimization procedure does not guarantee optimality of search process, several random starting points need to be generated and used as input into global search process. In order to construct powerful search procedure by guidance of global exploration, genetic algorithm was applied to scatter the set of quasi-local mimizers into global positions. Experimental results show that the proposed algorithm is feasible, and reaches obvious effects in terms of jacquard image segmentation.

Keywords

Image Segmentation Phase Field Phase Field Model Fuzzy Optimization Phase Field Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Zhilin Feng
    • 1
    • 2
  • Jianwei Yin
    • 1
  • Hui Zhang
    • 1
    • 2
  • Jinxiang Dong
    • 1
  1. 1.State Key Laboratory of CAD & CGZhejiang UniversityHangzhouP.R. China
  2. 2.College of ZhijiangZhejiang University of TechnologyHangzhouP.R. China

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