Color Image Segmentation Using a Semi-wrapped Gaussian Mixture Model

  • Anandarup Roy
  • Swapan K. Parui
  • Debyani Nandi
  • Utpal Roy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6744)


This article deals with color image segmentation in the hue-saturation-value space. Hue, saturation and value components are samples on a cylinder. A model for such data is provided by the semi-wrapped Gaussian distribution. Further its mixture is used to approximate the hue-saturation-value distribution. The mixture parameters are estimated using the standard EM algorithm. The results are obtained on Berkeley segmentation dataset. Comparisons are made with vM-Gauss mixture model, GMM and Mean-Shift procedures. Experimental results reveal improvement in segmentation by our method.


Mixture Model Gaussian Mixture Model Multivariate Gaussian Distribution Mixture Parameter Color Image Segmentation 
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 2011

Authors and Affiliations

  • Anandarup Roy
    • 1
  • Swapan K. Parui
    • 1
  • Debyani Nandi
    • 2
  • Utpal Roy
    • 3
  1. 1.CVPR UnitIndian Statistical InstituteKolkataIndia
  2. 2.School of Education Tech.Jadavpur UniversityKolkataIndia
  3. 3.Dept. of Computer & System SciencesVisva-Bharati UniversitySantiniketanIndia

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