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  • Research Article
  • Open Access
  • Ordinal-Measure Based Shape Correspondence

    • 1Email author,
    • 1,
    • 1,
    • 1 and
    • 1
    EURASIP Journal on Advances in Signal Processing20022002:124089

    https://doi.org/10.1155/S111086570200077X

    • Received: 31 July 2001
    • Published:

    Abstract

    We present a novel approach to shape similarity estimation based on distance transformation and ordinal correlation. The proposed method operates in three steps: object alignment, contour to multilevel image transformation, and similarity evaluation. This approach is suitable for use in shape classification, content-based image retrieval and performance evaluation of segmentation algorithms. The two latter applications are addressed in this papers. Simulation results show that in both applications our proposed measure performs quite well in quantifying shape similarity. The scores obtained using this technique reflect well the correspondence between object contours as humans perceive it.

    Keywords

    • shape
    • ordinal
    • correlation
    • content
    • retrieval
    • indexing
    • segmentation
    • performance

    Authors’ Affiliations

    (1)
    Signal Processing Laboratory, Tampere University of Technology, P.O. Box 553, Tampere, FIN-33101, Finland

    Copyright

    © Alaya Cheikh et al. 2002

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