DocumentCode :
603162
Title :
Trademark image retrieval by integrating shape with texture feature
Author :
Agrawal, Deepak ; Jalal, Anand Singh ; Tripathi, Rajeev
Author_Institution :
Dept. of Comput. Eng. & Applic., GLA Univ., Mathura, India
fYear :
2013
fDate :
9-10 March 2013
Firstpage :
30
Lastpage :
33
Abstract :
Trademark image retrieval is important to protect the copyright of registered trademark. A trademark play a significant role to distinguish the symbol or indicator used by an individual, commercial organization, or other authorized entity to recognize that the products or services to clients with which the trademark appears initiate from a unique source. However, measuring perceptual similarity and defining appropriate similarity measure between trademark images remain a challenging task. In this paper, we propose a method for trademark image retrieval which is based on shape and texture features of trademark images. Zernike moment and curvelet transform is used as shape and texture feature respectively. A weighted average distance is used for similarity measure. Results illustrate that combining shape feature with curvelet based texture feature performs well in precision.
Keywords :
Zernike polynomials; curvelet transforms; feature extraction; image retrieval; image texture; shape recognition; trademarks; Zernike moment; copyright protection; curvelet based texture feature; curvelet transform; feature extraction; registered trademark; similarity measure; trademark image retrieval; trademark image shape features; trademark image texture features; weighted average distance; Euclidean distance; Feature extraction; Image retrieval; Shape; Trademarks; Transforms; Trademark; Zernike moment; curvelet transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Systems and Computer Networks (ISCON), 2013 International Conference on
Conference_Location :
Mathura
Print_ISBN :
978-1-4673-5987-0
Type :
conf
DOI :
10.1109/ICISCON.2013.6524168
Filename :
6524168
Link To Document :
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