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Machine Vision and Applications

, Volume 27, Issue 2, pp 287–301 | Cite as

Logo localization and recognition in natural images using homographic class graphs

  • Raluca Boia
  • Corneliu Florea
  • Laura FloreaEmail author
  • Radu Dogaru
Original Paper

Abstract

We propose a method for localization and classification of brand logos in natural images. The system has to overcome multiple challenges such as perspective deformations, warping, variations of the shape and colors, occlusions, background variations. To deal with perspective variation, we rely on homography matching between the SIFT keypoints of logo instances of the same class. To address the changes in color, we construct a weighted graph of logo interconnections that is further analyzed to extract potentially multiple instances of the class. The main instance is built by grouping the keypoints of the graph connected logos onto the central image. The secondary instance is needed for color inverted logos and is obtained by inverting the orientation of the main instance. The constructed logo recognition system is tested on two databases (FlickrLogos-32 and BelgaLogos), outperforming state of the art with more than 10 % accuracy.

Keywords

Logo Localization Recognition Class model  Homography 

Notes

Acknowledgments

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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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Raluca Boia
    • 1
  • Corneliu Florea
    • 1
  • Laura Florea
    • 1
    Email author
  • Radu Dogaru
    • 2
  1. 1.Image Processing and Analysis LaboratoryUniversity Politehnica of BucharestBucharestRomania
  2. 2.Natural Computing LaboratoryUniversity Politehnica of BucharestBucharestRomania

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