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Evaluation of Color Image Segmentation Algorithms Based on Histogram Thresholding

  • Patrick Ndjiki-Nya
  • Ghislain Simo
  • Thomas Wiegand
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3893)

Abstract

Image segmentation is an essential processing step in texture analysis systems, as its accuracy has a significant impact on the quality of the final analysis result. The downside of texture analysis is that segmentation is one of the most difficult tasks in image processing. In this paper, algorithms for improved color image segmentation are presented. They are all based on a histogram thresholding approach that was developed for monochrome images for it has proven to be very effective. Improvements over the genuine segmentation approach are measured and the best optimization algorithm is determined.

Keywords

Receiver Operating Characteristic Curve Image Segmentation Segmentation Approach Texture Region Monochrome Image 
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

  • Patrick Ndjiki-Nya
    • 1
  • Ghislain Simo
    • 1
  • Thomas Wiegand
    • 1
  1. 1.Image Communication Group, Image Processing DepartmentFraunhofer Heinrich-Hertz-InstitutBerlinGermany

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