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Segmentation of mrf based image using hierarchical genetic algorithm

  • Jin Wook Kim
  • Eun Yi Kim
  • Se Hyun Park
  • Hang Joon Kim
Poster Session II
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1351)

Abstract

In this paper, a segmentation of an Markov Random Field based image is proposed. We use a hierarchical image model consists of color, blurring and noise parameters and define an energy function for proper image segmentation criterion. In general, it is not easy to search optimal parameter values which optimize the given energy function. To search optimal parameter values effectively, Hierarchical Genetic Algorithm is used and the experimental results show the effectiveness of the proposed method.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Jin Wook Kim
    • 1
  • Eun Yi Kim
    • 1
  • Se Hyun Park
    • 1
  • Hang Joon Kim
    • 1
  1. 1.Department of Computer EngineeringKyungPook National UniversityTaeguSouth Korea

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