Article ID Journal Published Year Pages File Type
534889 Pattern Recognition Letters 2008 9 Pages PDF
Abstract

A unique color space segmentation method is introduced. It is founded on features of human cognition, where 11 color categories are used in processing color. In two experiments, human subjects were asked to categorize color stimuli into these 11 color categories, which resulted in markers for a Color LookUp Table (CLUT). These CLUT markers are projected on two 2D projections of the HSI color space. By applying the newly developed Fast Exact Euclidean Distance (FEED) transform on the projections, a complete and efficient segmentation of color space is achieved. With that, a human-based color space segmentation is generated, which is invariant for intensity changes. Moreover, the efficiency of the procedure facilitates the generation of adaptable, application-centered, color quantization schemes. It is shown to work excellently for color analysis, texture analysis, and for Color-Based Image Retrieval purposes.

Related Topics
Physical Sciences and Engineering Computer Science Computer Vision and Pattern Recognition
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