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On the Use of Geometric Matching for Both: Isolated Symbol Recognition and Symbol Spotting

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Graphics Recognition. New Trends and Challenges (GREC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7423))

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Abstract

Symbol recognition is important in many applications such as the automated interpretation of line drawings and retrieval-by-content search engines. This paper presents the use of geometric matching for symbol recognition under similarity transformations. We incorporate this matching approach in a complete symbol recognition/spotting system, which consists of denoising, symbol representation and recognition. The proposed system works for both isolated recognition and spotting symbols in context. For denoising, we use an adaptive preprocessing algorithm. For symbol representation, pixels and/or vectorial primitives can be used, then the recognition is done via geometric matching. When applied on the datasets of GREC’05 and GREC’11 symbol recognition contests, the system has performed significantly better than other statistical or structural methods.

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Author information

Authors and Affiliations

  1. Technical University Kaiserslautern, Germany

    Nibal Nayef & Thomas M. Breuel

Authors
  1. Nibal Nayef
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  2. Thomas M. Breuel
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Chung-Ang University, 221 Heuksukdong, 156-756, Dongjakku, Seoul, Korea

    Young-Bin Kwon

  2. Laboratoire L3i, Université de La Rochelle, Avenue Michel Crépeau, 17042, La Rochelle Cedex 1, France

    Jean-Marc Ogier

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Nayef, N., Breuel, T.M. (2013). On the Use of Geometric Matching for Both: Isolated Symbol Recognition and Symbol Spotting. In: Kwon, YB., Ogier, JM. (eds) Graphics Recognition. New Trends and Challenges. GREC 2011. Lecture Notes in Computer Science, vol 7423. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36824-0_4

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  • DOI: https://doi.org/10.1007/978-3-642-36824-0_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36823-3

  • Online ISBN: 978-3-642-36824-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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