Evaluation of color image segmentation algorithms based on histogram thresholding

Authors:
Patrick Ndjiki-Nya;Ghislain Simo;Thomas Wiegand
Affiliations:
Image Communication Group, Image Processing Department, Fraunhofer Heinrich-Hertz-Institut, Berlin, Germany;Image Communication Group, Image Processing Department, Fraunhofer Heinrich-Hertz-Institut, Berlin, Germany;Image Communication Group, Image Processing Department, Fraunhofer Heinrich-Hertz-Institut, Berlin, Germany
Venue:
VLBV'05 Proceedings of the 9th international conference on Visual Content Processing and Representation
Year:
2005

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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.