Shape measures for content based image retrieval: a comparison
Information Processing and Management: an International Journal
Trademark shape recognition using closed contours
Pattern Recognition Letters
On the Accuracy of Zernike Moments for Image Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-Based Image Retrieval Using Fourier Descriptors on a Logo Database
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Evaluation of MPEG-7 shape descriptors against other shape descriptors
Multimedia Systems
Gestalt-based feature similarity measure in trademark database
Pattern Recognition
On the computational aspects of Zernike moments
Image and Vision Computing
Practice and challenges in trademark image retrieval
Proceedings of the 6th ACM international conference on Image and video retrieval
Hybrid Content-Based Trademark Retrieval Using Region and Contour Features
AINAW '08 Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops
Moment-Based Techniques for Image Retrieval
DEXA '08 Proceedings of the 2008 19th International Conference on Database and Expert Systems Application
Trademark Image Retrieval Using Region Zernike Moments
IITA '08 Proceedings of the 2008 Second International Symposium on Intelligent Information Technology Application - Volume 02
Trademark Image Retrieval Using Wavelet-based Shape Features
IITAW '08 Proceedings of the 2008 International Symposium on Intelligent Information Technology Application Workshops
Shape feature matching for trademark image retrieval
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
Unsupervised image retrieval framework based on rule base system
Expert Systems with Applications: An International Journal
Balancing deformability and discriminability for shape matching
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Fast K-means algorithm based on a level histogram for image retrieval
Expert Systems with Applications: An International Journal
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Trademarks are distinctive visual symbols with high reputational value, due to the perception of quality and innovation associated with them. They are important reputational assets used as a marketing tool to convey a certain assurance of quality, innovation, and the standards, which the manufacturer seeks to maintain. This motivates the need for trademark protection by providing a solution to prevent infringement. This problem can be addressed by developing retrieval systems capable of comparing the visual similarity of trademarks. This paper contributes to the research in this field by proposing an innovative trademark retrieval technique with improved retrieval performance due to the integration of global and local descriptors. The global descriptor employed is the Zernike moment's coefficients. The local descriptor is the edge-gradient co-occurrence matrix, derived from the contour information that is considered very important in human perception of visual similarity. The proposed retrieval technique is tested using the standard MPEG-7 shape database of 1400 images and the MPEG-7 trademark database of 3260 images. The results show 5% precision/recall improvement in the case of the MPEG-7 shape database, as well as 2.35% Bull's eye score improvement and 19.8% NMRR score improvement for the 10 randomly selected trademarks from the MPEG-7 trademarks database.