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  • Structure Integral Transform Versus Radon Transform: A 2D Mathematical Tool for Invariant Shape Recognition

    Author(s)
    Wang, Bin
    Gao, Yongsheng
    Griffith University Author(s)
    Gao, Yongsheng
    Wang, Bin
    Year published
    2016
    Metadata
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    Abstract
    Abstract: In this paper, we present a novel mathematical tool, Structure Integral Transform (SIT), for invariant shape description and recognition. Different from the Radon Transform (RT), which integrates the shape image function over a 1D line in the image plane, the proposed SIT builds upon two orthogonal integrals over a 2D K-cross dissecting structure spanning across all rotation angles by which the shape regions are bisected in each integral. The proposed SIT brings the following advantages over the RT: 1) it has the extra function of describing the interior structural relationship within the shape which provides a ...
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    Abstract: In this paper, we present a novel mathematical tool, Structure Integral Transform (SIT), for invariant shape description and recognition. Different from the Radon Transform (RT), which integrates the shape image function over a 1D line in the image plane, the proposed SIT builds upon two orthogonal integrals over a 2D K-cross dissecting structure spanning across all rotation angles by which the shape regions are bisected in each integral. The proposed SIT brings the following advantages over the RT: 1) it has the extra function of describing the interior structural relationship within the shape which provides a more powerful discriminative ability for shape recognition; 2) the shape regions are dissected by the K-cross in a coarse to fine hierarchical order that can characterize the shape in a better spatial organization scanning from the center to the periphery; and 3) it is easier to build a completely invariant shape descriptor. The experimental results of applying SIT to shape recognition demonstrate its superior performance over the well-known Radon transform, and the well-known shape contexts and the polar harmonic transforms.
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    Journal Title
    IEEE Transactions on Image Processing
    Volume
    25
    Issue
    12
    DOI
    https://doi.org/10.1109/TIP.2016.2609816
    Subject
    Artificial Intelligence and Image Processing not elsewhere classified
    Artificial Intelligence and Image Processing
    Electrical and Electronic Engineering
    Cognitive Sciences
    Publication URI
    http://hdl.handle.net/10072/101194
    Collection
    • Journal articles

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