Color image segmentation: advances and prospects |
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Authors: | H. D. X. H. Y. Jingli |
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Affiliation: | Department of Computer Science, Utah State University, Logan, UT 84322-4205, USA |
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Abstract: | Image segmentation is very essential and critical to image processing and pattern recognition. This survey provides a summary of color image segmentation techniques available now. Basically, color segmentation approaches are based on monochrome segmentation approaches operating in different color spaces. Therefore, we first discuss the major segmentation approaches for segmenting monochrome images: histogram thresholding, characteristic feature clustering, edge detection, region-based methods, fuzzy techniques, neural networks, etc.; then review some major color representation methods and their advantages/disadvantages; finally summarize the color image segmentation techniques using different color representations. The usage of color models for image segmentation is also discussed. Some novel approaches such as fuzzy method and physics-based method are investigated as well. |
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Keywords: | Color image segmentation Color representations Color space transformations Neural networks Thresholding Clustering Edge detection Region-based approach Physics based approach Fuzzy logic |
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