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Geometric Invariant Curve and Surface Normalization

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Image Analysis and Recognition (ICIAR 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4142))

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Abstract

In this work, a geometric invariant curve and surface normalization method is presented. Translation, scale and shear are normalized by Principal Component Analysis (PCA) whitening. Independent Component Analysis (ICA) and the third order moments are then employed for rotation and reflection normalization. By applying this normalization, curves and surfaces that are related by geometric transformations (affine or rigid) can be transformed into a canonical representation. Proposed technique is verified with several 2D and 3D object matching and recognition experiments.

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Author information

Authors and Affiliations

  1. Institute of Informatics, Istanbul Technical University, Maslak, Istanbul, Turkey

    Sait Sener

  2. Faculty of Engineering and Natural Sciences, Sabanci University, Orhanli-Tuzla, 34956, Istanbul, Turkey

    Mustafa Unel

Authors
  1. Sait Sener
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  2. Mustafa Unel
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Editor information

Editors and Affiliations

  1. Faculty of Engineering, Institute of Biomedical Engineering, Rua Dr. Roberto Frias, University of Porto, 4200-465, Porto, Portugal

    Aurélio Campilho

  2. Electrical and Computer Engineering Department, University of Waterloo,  

    Mohamed Kamel

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© 2006 Springer-Verlag Berlin Heidelberg

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Sener, S., Unel, M. (2006). Geometric Invariant Curve and Surface Normalization. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2006. Lecture Notes in Computer Science, vol 4142. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11867661_40

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  • DOI: https://doi.org/10.1007/11867661_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44894-5

  • Online ISBN: 978-3-540-44896-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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