Modeling human color categorization

Authors:
E. L. van den Broek;Th. E. Schouten;P. M. F. Kisters
Affiliations:
Center for Telematics and Information Technology, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands;Institute for Computing and Information Science, Radboud University Nijmegen, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands;GX Creative Online Development B.V., Wijchenseweg 111, 6538 SW Nijmegen, The Netherlands
Venue:
Pattern Recognition Letters
Year:
2008

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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.