Computing color categories

S.N. Yendrikhovskij

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

    10 Citaten (Scopus)


    This paper is an attempt to develop a coherent framework for understanding, modeling, and computing color categories. The main assumption is that the structure of color category systems originates from the statistical structure of the perceived color environment. This environment can be modeled as color statistics of natural images in some perceptual and approximately uniform color space (e.g., the CIELUV color space). The process of color categorization can be modeled as the grouping of the color statistics by clustering algorithms (e.g., K-means). The proposed computational model enable to predict the location, order, and number of color categories. The model is examined on the basis of K-means clustering analysis of statistics of 630 natural images in the CIELUV color space. In general, the predictions are consistent with Berlin and Kai, and Boynton and Oslon2 data.
    Originele taal-2Engels
    TitelHuman Vision and Electronic Imaging V, January 24-27, 2000, San Jose, USA
    RedacteurenB.E. Rogowitz, T.N. Pappas
    Plaats van productieBellingham
    StatusGepubliceerd - 2000
    Evenementconference; Human vision and Electronic Imaging V; 2000-01-24; 2000-01-27 -
    Duur: 24 jan. 200027 jan. 2000

    Publicatie series

    NaamProceedings of SPIE
    ISSN van geprinte versie0277-786X


    Congresconference; Human vision and Electronic Imaging V; 2000-01-24; 2000-01-27
    AnderHuman vision and Electronic Imaging V


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