In this paper a new skin detection method based on adaptive thresholds is proposed. Compared with the fixed threshold histogram method used widely, ours can find optimal thresholds to the different complex backgrounds. Four clues are summarized from the skin probability distribution histogram (SPDH) to help search candidates of optimum thresholds, and an ANN classifier is trained to select the final optimum threshold. A color deviation histogram (CDH) is also proposed to eliminate confusing backgrounds and refine optimal thresholds. The selection process of optimal thresholds is fast thus appropriate for real-time applications since no iterative operation is involved. Experimental results show that the proposed method can achieve better performance than the fixed threshold histogram method.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    An adaptive skin color detection algorithm with confusing backgrounds elimination


    Contributors:
    Ming-Ji Zhang, (author) / Wen Gao, (author)


    Publication date :

    2005-01-01


    Size :

    383373 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    An Adaptive Skin Color Detection algorithm with Confusing Backgrounds Elimination

    Zhang, M.-J. / Gao, W. | British Library Conference Proceedings | 2005


    Identification of confusing objects for color deficient vision

    BOND JACOB ALAN / SZCZERBA JOSEPH F / WEISS JOHN P | European Patent Office | 2024

    Free access

    IDENTIFICATION OF CONFUSING OBJECTS FOR COLOR DEFICIENT VISION

    BOND JACOB ALAN / SZCZERBA JOSEPH F / WEISS JOHN P | European Patent Office | 2024

    Free access

    GHS too confusing to apply?

    Online Contents | 2008


    GHS too confusing to apply?

    British Library Online Contents | 2008