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    University of Taipei > 理學院 > 資訊科學系 > 期刊論文 >  Item 987654321/15891


    請使用永久網址來引用或連結此文件: http://utaipeir.lib.utaipei.edu.tw/dspace/handle/987654321/15891


    題名: Contrast Compensation by Fuzzy Classification and Image Illumination Analysis for Back-lit and Front-lit Color Face Images
    作者: Tsai, C. M.;蔡俊明;Yeh, Z. M.
    貢獻者: 臺北市立教育大學資訊科學系
    日期: 2010-08
    上傳時間: 2017-07-25 09:58:38 (UTC+8)
    摘要: Conventional contrast enhancement methods
    have two shortcomings. First, most of them do not produce
    satisfactory enhancement results for face images with back-lit
    or front-lit. Second, most of them need transformation
    functions and parameters which are specified manually. Thus,
    this paper proposes an automatic and parameter-free contrast
    compensation algorithm for skin detection in color face
    images. This method includes following steps: First, RGB
    color space is transformed to YIQ color space. Second, fuzzy
    logic is used to classify the color images into three categories:
    back-lit, normal-lit, and front-lit. Third, image illumination
    analysis is used to analyze the image distribution. Fourth, the
    input image is compensated by piecewise linear based
    enhancement method. Finally, the compensation image is
    transformed back to RGB color space. Our experiments
    included various color and gray face images. Experiment
    results show that the performance of the proposed
    compensation method is better than other available methods
    in skin detection and visual perception measurements
    關聯: IEEE Transactions on Consumer Electronics, Vol. 56, No. 3, pp. 1570-1578
    顯示於類別:[資訊科學系] 期刊論文

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