Shape Descriptor Based on the Volume of Transformed Image Boundary

  • Xavier Descombes
  • Sergey Komech
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6744)


In this paper, we derive new shape descriptors based on a directional characterization. The main idea is to study the behavior of the shape neighborhood under family of transformations. We obtain a description invariant with respect to rotation, reflection, translation and scaling. We consider family of volume-preserving transformations. Our descriptor is based on the volume of the neighbourhood of transformed image. A well-defined metric is then proposed on the associated feature space. We show the continuity of this metric. Some results on shape retrieval are provided on Kimia 216 and part of MPEG-7 CE-Shape-1 databases to show the accuracy of the proposed shape metric.


Image Retrieval Shape Descriptor Shape Space Shape Retrieval Procrustes Distance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Xavier Descombes
    • 1
  • Sergey Komech
    • 2
  1. 1.EPI Ariana, INRIA SAMSophia AntipolisFrance
  2. 2.Dobrushin Lab.IITPMoscowRussia

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