Unsupervised Perceptual Segmentation of Natural Color Images Using Fuzzy-Based Hierarchical Algorithm

  • Junji Maeda
  • Akimitsu Kawano
  • Sato Saga
  • Yukinori Suzuki
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4522)


This paper proposes unsupervised perceptual segmentation of natural color images using a fuzzy-based hierarchical algorithm. L  ⋆  a  ⋆  b  ⋆  color space is used to represent color features and statistical geometrical features are adopted as texture features. A fuzzy-based homogeneity measure makes a fusion of color features and texture features. Proposed hierarchical segmentation method is performed in four stages: simple splitting, local merging, global merging and boundary refinement. Experiments on segmentation of natural color images are presented to verify the effectiveness of the proposed method in obtaining perceptual segmentation.


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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Junji Maeda
    • 1
  • Akimitsu Kawano
    • 1
  • Sato Saga
    • 1
  • Yukinori Suzuki
    • 1
  1. 1.Muroran Institute of Technology, Muroran 050-8585Japan

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