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Three-Dimensional Object Recognition Using a Modified Exoskeleton and Extended Hausdorff Distance Matching Algorithm

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Image Analysis and Recognition (ICIAR 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3211))

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Abstract

This paper presents a simple but efficient matching methodology for three-dimensional object recognition using a modified exoskeleton (mES) and Hausdorff distance transform. The aim of this paper is to propose a method that can be used in computer vision system for robots or in digital image retrieval. The most significant part of this method is that it is less susceptible to distortion caused by noise and it is also rotation and translation invariant. The effectiveness of the proposed method is evaluated by implementing the method on three-dimensional object recognition where the mES of an observed object is compared against the mES of each training object in the database and the similarity between the two objects is measured using the extended Hausdorff distance matching algorithm. ...

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References

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Author information

Authors and Affiliations

  1. Mathematics Department, Faculty of Science, Chulalongkorn University, Phatumwan, Bangkok, 10330, Thailand

    Rajalida Lipikorn

  2. Graduate School of BASE, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei-shi, Tokyo, 184-8588, Japan

    Akinobu Shimizu & Hidefumi Kobatake

Authors
  1. Rajalida Lipikorn
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  2. Akinobu Shimizu
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  3. Hidefumi Kobatake
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Editor information

Editors and Affiliations

  1. FEUP - Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio Campilho

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

    Mohamed Kamel

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© 2004 Springer-Verlag Berlin Heidelberg

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Lipikorn, R., Shimizu, A., Kobatake, H. (2004). Three-Dimensional Object Recognition Using a Modified Exoskeleton and Extended Hausdorff Distance Matching Algorithm. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30125-7_86

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  • DOI: https://doi.org/10.1007/978-3-540-30125-7_86

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23223-0

  • Online ISBN: 978-3-540-30125-7

  • eBook Packages: Springer Book Archive

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