Color image segmentation: advances and prospects

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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.

论文关键词:Color image segmentation,Color representations,Color space transformations,Neural networks,Thresholding,Clustering,Edge detection,Region-based approach,Physics based approach,Fuzzy logic

论文评审过程:Received 23 February 2000, Accepted 12 September 2000, Available online 30 August 2001.

论文官网地址:https://doi.org/10.1016/S0031-3203(00)00149-7