Performance impact of ordinal ranking on content fingerprinting

Content fingerprinting provides a compact representation of multimedia objects for copy identification. This paper analyzes the impact of the ordinal-ranking based feature encoding on the performance of content fingerprinting. Expressions are derived for the identification performance of a fingerprinting system with and without ordinal ranking. The analysis indicates that when the number of features is moderately large, ordinal ranking can improve the robustness of the fingerprinting system to large distortions of the features and significantly increase the probability of detection. These results enhance understandings of ordinal ranking and provide design guidelines for choosing different system parameters to achieve a desired identification accuracy.

[1]  Min Wu,et al.  Modeling and analysis of ordinal ranking in content fingerprinting , 2009, 2009 First IEEE International Workshop on Information Forensics and Security (WIFS).

[2]  Jian Lu,et al.  Video fingerprinting for copy identification: from research to industry applications , 2009, Electronic Imaging.

[3]  Min Wu,et al.  A decision theoretic framework for analyzing binary hash-based content identification systems , 2008, DRM '08.

[4]  Rakesh Mohan,et al.  Video sequence matching , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[5]  Min Wu,et al.  A framework for theoretical analysis of content fingerprinting , 2010, Electronic Imaging.