Image Segmentation by Deterministic Annealing Algorithm with Adaptive Spatial Constraints

  • Xulei Yang
  • Aize Cao
  • Qing Song
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)


In this paper, we present an adaptive spatially-constrained deterministic annealing (ASDA) algorithm, which takes into account the spatial continuity constraints by using a dissimilarity index that allows spatial interactions between image pixels, for image segmentation. The local spatial continuity constraint reduces the noise effect and the classification ambiguity. More importantly, the strength of spatial constraint for each given image pixel is auto-selected by the scaled variance of its neighbor pixels, which results in the adaptiveness of the presented algorithm. The effectiveness and efficiency of the presented method for image segmentation are supported by experimental results on synthetic and MR images.


Image Segmentation Segmentation Result Segmentation Accuracy Adaptive Selection Fuzzy Cluster Algorithm 
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 2006

Authors and Affiliations

  • Xulei Yang
    • 1
  • Aize Cao
    • 2
  • Qing Song
    • 1
  1. 1.EEE SchoolNanyang Technological UniversitySingapore
  2. 2.Medical CenterVanderbilt UniversityUSA

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