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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/2056


    Title: Color Texture Segmentation for Clothing Based on Finite Prolate Spheroidal Sequences
    Authors: Ling-Ling Wang;Chih Chung Chien
    Contributors: Department of Information Communication, Asia University
    Keywords: finite prolate spheroidal sequencescolor quantization;texture segmentationlocal centroid clustering
    Date: 2007-01
    Issue Date: 2009-10-13 14:58:12 (UTC+8)
    Publisher: Asia University
    Abstract: By means of a computer-aided fashion design system, a fashion designer can easily make changes
    to the various colors, textures and pattern prints of clothing design, and thus need not draw on paper a
    great number of drafts. One of the most difficult tasks in a computer-aided fashion design system is to
    separate the clothing of interest on a model from the background, so that changes can be applied to the
    material. There exist folds, shadows, diverse textures, etc. on the clothing which make the segmentation
    work difficult. In this paper, a color texture segmentation method for clothing segmentation is proposed.
    Color quantization is first performed to reduce the number of colors and shadow/highlight effects on
    the image. The color texture features are then extracted based on the finite prolate spheroidal sequences.
    By these features, a hierarchical coarse-to-fine segmentation method is used to separate the clothing
    from the backgrounds. Finally, post-processing is applied to obtain a smooth clothing boundary.
    Satisfactory experimental results have been achieved using the proposed approach.
    Relation: Asian Journal of Health and Information Sciences 1(4):425-445
    Appears in Collections:[Asian Journal of Health and Information Sciences] v.1 n.4

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