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Abstract and Applied Analysis
Volume 2014, Article ID 854516, 8 pages
Research Article

A Comparison of Moments-Based Logo Recognition Methods

1Computer Application Research Center, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055, China
2Shenzhen Applied Technology Engineering Laboratory for Internet Multimedia Application, Shenzhen 518055, China
3Department of Computer Science, COMSATS Institute of Information Technology, Abbottabad 22010, Pakistan

Received 26 May 2014; Revised 26 July 2014; Accepted 26 July 2014; Published 12 August 2014

Academic Editor: Sher Afzal Khan

Copyright © 2014 Zili Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Logo recognition is an important issue in document image, advertisement, and intelligent transportation. Although there are many approaches to study logos in these fields, logo recognition is an essential subprocess. Among the methods of logo recognition, the descriptor is very vital. The results of moments as powerful descriptors were not discussed before in terms of logo recognition. So it is unclear which moments are more appropriate to recognize which kind of logos. In this paper we find out the relations between logos with different transforms and moments, which moments are fit for logos with different transforms. The open datasets are employed from the University of Maryland. The comparisons based on moments are carried out from the aspects of logos with noise, and rotation, scaling, rotation and scaling.