Trademarks recognition based on local regions similarities

Ahmed Zeggari, Fella Hachouf, Sebti Foufou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper deals with content based image retrieval. We propose a logo recognition algorithm based on local regions, where the trademark (or logo) image is segmented by the clustering of points of interest obtained by Harris corners detector. The minimum rectangle surrounding each cluster is detected forming the regions of interest. Global features such as Hu moments and histograms of each local region are combined to find similar logos in the database. Similarity is measured based on the integrated minimum average distance of the individual components. The results obtained demonstrate tolerance to logos distortions such as rotation, occlusion and noise.

Original languageEnglish (US)
Title of host publication10th International Conference on Information Sciences, Signal Processing and their Applications, ISSPA 2010
Pages37-40
Number of pages4
DOIs
StatePublished - 2010
Event10th International Conference on Information Sciences, Signal Processing and their Applications, ISSPA 2010 - Kuala Lumpur, Malaysia
Duration: May 10 2010May 13 2010

Publication series

Name10th International Conference on Information Sciences, Signal Processing and their Applications, ISSPA 2010

Other

Other10th International Conference on Information Sciences, Signal Processing and their Applications, ISSPA 2010
CountryMalaysia
CityKuala Lumpur
Period5/10/105/13/10

Keywords

  • Clustering
  • Image color analysis
  • Image segmentation
  • Information retrieval
  • Moments
  • Pattern recognition

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Signal Processing

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  • Cite this

    Zeggari, A., Hachouf, F., & Foufou, S. (2010). Trademarks recognition based on local regions similarities. In 10th International Conference on Information Sciences, Signal Processing and their Applications, ISSPA 2010 (pp. 37-40). [5605559] (10th International Conference on Information Sciences, Signal Processing and their Applications, ISSPA 2010). https://doi.org/10.1109/ISSPA.2010.5605559