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

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Book cover Computer Analysis of Images and Patterns (CAIP 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6854))

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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.

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Author information

Authors and Affiliations

  1. Dipartimento di Matematica, Università di Bologna, Italy

    Patrizio Frosini

  2. DiSMI, Università di Modena e Reggio Emilia, Italy

    Claudia Landi

  3. ARCES, Università di Bologna, Italy

    Patrizio Frosini & Claudia Landi

Authors
  1. Patrizio Frosini
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  2. Claudia Landi
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Editor information

Editors and Affiliations

  1. Dpto. Matematica Aplicada I, Escuaela Técnica Superior de Ingeniería Informática, Universite de Sevilla, Avda. Reina Mercedes, s/n, 41012, Sevilla, Spain

    Pedro Real

  2. Departamento de Matemática Aplicada I, Escuela Técnica Superior de Ingeniería Informática, University of Seville, Avenida Reina Mercedes s/n, 41012, Sevilla, Spain

    Daniel Diaz-Pernil  & Helena Molina-Abril  & 

  3. Departamento de Didáctica de la Mathemática y de las CC.Experimentales, Universidad del País Vasco-Esukal Herriko Unibertsitatea, Escuela Universitaria de Magisterio, Ramón y Cajal, 72, 48014, Bilbao (Bizcaia), Spain

    Ainhoa Berciano

  4. Institute of Computer Graphics and Algorithms, Pattern Recognition and Image Processing Group, Vienna University of Technology, Favoritenstraße 9/186-3, 1040, Vienna, Austria

    Walter Kropatsch

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© 2011 Springer-Verlag Berlin Heidelberg

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Frosini, P., Landi, C. (2011). Persistent Betti Numbers for a Noise Tolerant Shape-Based Approach to Image Retrieval. In: Real, P., Diaz-Pernil, D., Molina-Abril, H., Berciano, A., Kropatsch, W. (eds) Computer Analysis of Images and Patterns. CAIP 2011. Lecture Notes in Computer Science, vol 6854. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23672-3_36

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  • DOI: https://doi.org/10.1007/978-3-642-23672-3_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23671-6

  • Online ISBN: 978-3-642-23672-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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