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International Conference on Computer Analysis of Images and Patterns

CAIP 2011: Computer Analysis of Images and Patterns pp 34–41Cite as

Robustness and Modularity of 2-Dimensional Size Functions – An Experimental Study

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

Abstract

This paper deals with the concepts of 2-dimensional size function and 2-dimensional matching distance. These are two ingredients of (2-dimensional) Size Theory, a geometrical/topological approach to shape analysis and comparison. 2-dimensional size functions are shape descriptors providing a signature of the shapes under study, while the 2-dimensional distance is the tool to compare them. The aim of the present paper is to validate, through some experiments on 3D-models, a computational framework recently introduced to deal with 2-dimensional Size Theory. We will show that the cited framework is modular and robust with respect to noise, non-rigid and non-metric-preserving shape transformations. The proposed framework allows us to improve the ability of 2-dimensional size functions in discriminating between shapes.

Partially supported by the CNR activities DG.RSTL.050.008, ICT.P10.009.001 and the Austrian Science Fund (FWF) grant no. P20134-N13.

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Author information

Authors and Affiliations

  1. IMATI, Consiglio Nazionale delle Ricerche, Genova, Italy

    Silvia Biasotti & Daniela Giorgi

  2. Vienna University of Technology, Faculty of Informatics, Pattern Recognition and Image Processing Group, Austria

    Andrea Cerri

Authors
  1. Silvia Biasotti
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  2. Andrea Cerri
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  3. Daniela Giorgi
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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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Biasotti, S., Cerri, A., Giorgi, D. (2011). Robustness and Modularity of 2-Dimensional Size Functions – An Experimental Study. 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_5

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  • DOI: https://doi.org/10.1007/978-3-642-23672-3_5

  • 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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