Color image segmentation in color and spatial domain

Authors:
Tie Qi Chen;Yi L. Murphey;Robert Karlsen;Grant Gerhart
Affiliations:
VisiTek, Inc., Harbrooke Ann Arbor, Michigan;VisiTek, Inc., Harbrooke Ann Arbor, Michigan;U. S. TACOM, Warren, MI and Department of Electrical and Computer Engineering, The University of Michigan-Dearborn, Dearborn, Michigan;U. S. TACOM, Warren, MI and Department of Electrical and Computer Engineering, The University of Michigan-Dearborn, Dearborn, Michigan
Venue:
IEA/AIE'2003 Proceedings of the 16th international conference on Developments in applied artificial intelligence
Year:
2003

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Abstract

In this paper we describe a color image segmentation system that performs color clustering in a color space followed by a color region segmentation algorithm in the image domain. In color space, we describe two different algorithms that clusters similar colors using different measuring criteria and present our evaluation results on these two algorithms in comparison with three well-known color segmentation algorithms. The region segmentation algorithm merges clusters in the image domain based on color similarity and spatial adjacency. We developed three different methods for merging regions in the image domain. The proposed clustering algorithms are applicable to color image indexing and retrieval, object segmentation using color feature and color image mining. The color image segmentation system has been implemented and tested on a variety of color images including satellite images, moving car images and etc. The system has shown to be both effective and efficient.