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  • Segmentation of Color Lip Images by Spatial Fuzzy Clustering

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    Author(s)
    Liew, AWC
    Leung, SH
    Lau, WH
    Griffith University Author(s)
    Liew, Alan Wee-Chung
    Year published
    2003
    Metadata
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    Abstract
    In this paper, we describe the application of a novel spatial fuzzy clustering algorithm to the lip segmentation problem. The proposed spatial fuzzy clustering algorithm is able to take into account both the distributions of data in feature space and the spatial interactions between neighboring pixels during clustering. By appropriate pre- and postprocessing utilizing the color and shape properties of the lip region, successful segmentation of most lip images is possible. Comparative study with some existing lip segmentation algorithms such as the hue filtering algorithm and the fuzzy entropy histogram thresholding algorithm ...
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    In this paper, we describe the application of a novel spatial fuzzy clustering algorithm to the lip segmentation problem. The proposed spatial fuzzy clustering algorithm is able to take into account both the distributions of data in feature space and the spatial interactions between neighboring pixels during clustering. By appropriate pre- and postprocessing utilizing the color and shape properties of the lip region, successful segmentation of most lip images is possible. Comparative study with some existing lip segmentation algorithms such as the hue filtering algorithm and the fuzzy entropy histogram thresholding algorithm has demonstrated the superior performance of our method.
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    Journal Title
    IEEE Transactions on Fuzzy Systems
    Volume
    11
    Issue
    4
    Publisher URI
    http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=91
    DOI
    https://doi.org/10.1109/TFUZZ.2003.814843
    Copyright Statement
    © 2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
    Subject
    Applied Mathematics
    Artificial Intelligence and Image Processing
    Electrical and Electronic Engineering
    Publication URI
    http://hdl.handle.net/10072/21808
    Collection
    • Journal articles

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