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Homographic Class Template for Logo Localization and Recognition

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Pattern Recognition and Image Analysis (IbPRIA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9117))

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Abstract

We propose a method for localizing and recognizing brand logos in natural images. The task is extremely challenging, due to the various changes in the appearance of the logos. We construct class templates by matching features between examples of the same class to build homographies. An interconnections graph is developed for each class and the representative points are added to the class model. Finally, each class is depicted by the reunion of the suitable keypoints and descriptors, thus leading to a high precision of the proposed logo recognition system. Results show that we outperform the state of the art systems on the challenging Flickr-32 database.

R. Boia—This work was supported by the Romanian Sectoral Operational Programme Human Resources Development 2007-2013 through the European Social Fund Financial Agreements POSDRU/159/1.5/S/132395 and POSDRU/159/1.5/S/134398.

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Author information

Authors and Affiliations

  1. University Politehnica of Bucharest, Bucharest, Romania

    Raluca Boia & Corneliu Florea

Authors
  1. Raluca Boia
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  2. Corneliu Florea
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Corresponding author

Correspondence to Raluca Boia .

Editor information

Editors and Affiliations

  1. Universitat Politècnica de València, València, Spain

    Roberto Paredes

  2. Universidade do Porto, Porto, Portugal

    Jaime S. Cardoso

  3. Universidade de Santiago de Compostela, Santiago de Compostela, Spain

    Xosé M. Pardo

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Boia, R., Florea, C. (2015). Homographic Class Template for Logo Localization and Recognition. In: Paredes, R., Cardoso, J., Pardo, X. (eds) Pattern Recognition and Image Analysis. IbPRIA 2015. Lecture Notes in Computer Science(), vol 9117. Springer, Cham. https://doi.org/10.1007/978-3-319-19390-8_55

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  • DOI: https://doi.org/10.1007/978-3-319-19390-8_55

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19389-2

  • Online ISBN: 978-3-319-19390-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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