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Persistent Betti Numbers for a Noise Tolerant Shape-Based Approach to Image Retrieval

  • Patrizio Frosini
  • Claudia Landi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6854)

Abstract

In content-based image retrieval a major problem is the presence of noisy shapes. It is well known that persistent Betti numbers are a shape descriptor that admits a dissimilarity distance, the matching distance, stable under continuous shape deformations. In this paper we focus on the problem of dealing with noise that changes the topology of the studied objects. We present a general method to turn persistent Betti numbers into stable descriptors also in the presence of topological changes. Retrieval tests on the Kimia-99 database show the effectiveness of the method.

Keywords

Multidimensional persistent homology Hausdorff distance symmetric difference distance 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Patrizio Frosini
    • 1
    • 3
  • Claudia Landi
    • 2
    • 3
  1. 1.Dipartimento di MatematicaUniversità di BolognaItaly
  2. 2.DiSMIUniversità di Modena e Reggio EmiliaItaly
  3. 3.ARCESUniversità di BolognaItaly

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