Evaluation of color representation for texture analysis

R. Verbrugge (Editor), Egon van den Broek, E.M. van Rikxoort, N. Taatgen (Editor), L. Schomaker (Editor)

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    Since more than 50 years texture in image material is a topic of research. Hereby, color was ignored mostly. This study compares 70 different configurations for texture analysis, using four features. For the configurations we used: (i) a gray value texture descriptor: the co-occurrence matrix and a color texture descriptor: the color correlogram, (ii) six color spaces, and (iii) several quantization schemes. A three classifier combination was used to classify the output of the configurations on the VisTex texture database. The results indicate that the use of a coarse HSV color space quantization can substantially improve texture recognition compared to various other gray and color quantization schemes.
    Original languageUndefined
    Number of pages8
    Publication statusPublished - 21 Oct 2004
    Event16th Belgium-Dutch Conference on Artificial Intelligence, BNAIC 2004 - Groningen, Netherlands
    Duration: 21 Oct 200422 Oct 2004
    Conference number: 16


    Conference16th Belgium-Dutch Conference on Artificial Intelligence, BNAIC 2004
    Abbreviated titleBNAIC


    • HMI-VRG: Virtual Reality and Graphics
    • Texture
    • Pattern Recognition
    • co-occurence matrix
    • color correlogram
    • Color
    • HMI-CI: Computational Intelligence
    • HMI-HF: Human Factors
    • IR-79317
    • Classification
    • Evaluation
    • EWI-21117

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