Open Access

Ordinal-Measure Based Shape Correspondence

  • Faouzi Alaya Cheikh1Email author,
  • Bogdan Cramariuc1,
  • Mari Partio1,
  • Pasi Reijonen1 and
  • Moncef Gabbouj1
EURASIP Journal on Advances in Signal Processing20022002:124089

https://doi.org/10.1155/S111086570200077X

Received: 31 July 2001

Published: 30 April 2002

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

Copyright

© Alaya Cheikh et al. 2002