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  • Fuzzy Image Clustering Incorporating Spatial Continuity

    Author(s)
    Liew, AWC
    Leung, SH
    Lau, WH
    Griffith University Author(s)
    Liew, Alan Wee-Chung
    Year published
    2000
    Metadata
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    Abstract
    The authors present a spatial fuzzy clustering algorithm that exploits the spatial contextual information in image data. The objective functional of their method utilises a new dissimilarity index that takes into account the influence of the neighbouring pixels on the centre pixel in a 3×1 window. The algorithm is adaptive to the image content in the sense that influence from the neighbouring pixels is suppressed in nonhomogeneous regions in the image. A cluster merging scheme that merges two clusters based on their closeness and their degree of overlap is presented. Through this merging scheme, an `optimal' number of clusters ...
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    The authors present a spatial fuzzy clustering algorithm that exploits the spatial contextual information in image data. The objective functional of their method utilises a new dissimilarity index that takes into account the influence of the neighbouring pixels on the centre pixel in a 3×1 window. The algorithm is adaptive to the image content in the sense that influence from the neighbouring pixels is suppressed in nonhomogeneous regions in the image. A cluster merging scheme that merges two clusters based on their closeness and their degree of overlap is presented. Through this merging scheme, an `optimal' number of clusters can be determined automatically as iteration proceeds. Experimental results with synthetic and real images indicate that the proposed algorithm is more tolerant to noise, better at resolving classification ambiguity and coping with different cluster shape and size than the conventional fuzzy c-means algorithm
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    Journal Title
    IEE Proceedings-Vision, Image and Signal Processing
    Volume
    147
    Issue
    2
    Publisher URI
    http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=848581
    DOI
    https://doi.org/10.1049/ip-vis:20000218
    Subject
    Artificial Intelligence and Image Processing
    Electrical and Electronic Engineering
    Cognitive Sciences
    Publication URI
    http://hdl.handle.net/10072/60815
    Collection
    • Journal articles

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