Comparison of distance measures for video copy detection

Content-based copy detection (CBCD) is a complementary approach to watermarking for detecting copies of media. Watermarking relies on the ability to detect from a copy a distinct pattern that was introduced into the original media. CBCD techniques detect copies by measuring distances between content-based signatures extracted from the original and the copy. The critical challenge in content-based copy detection is the design of signatures, which are invariant to the differences in quality across copies of the same media (resolution, compression and digitization effects). Most of the distance measures used in image retrieval have been developed without much consideration to these types of variations between copies. This paper examines the use of several image distance measures in the context of video copy detection and compares their performances.

[1]  Milind R. Naphade,et al.  Novel scheme for fast and efficent video sequence matching using compact signatures , 1999, Electronic Imaging.

[2]  Xavier Binefa,et al.  Color normalization for appearance based recognition of video key-frames , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[3]  Majid Ahmadi,et al.  Pattern recognition with moment invariants: A comparative study and new results , 1991, Pattern Recognit..

[4]  Edward Y. Chang,et al.  RIME: a replicated image detector for the World Wide Web , 1998, Other Conferences.

[5]  Wolfgang Effelsberg,et al.  On the detection and recognition of television commercials , 1997, Proceedings of IEEE International Conference on Multimedia Computing and Systems.

[6]  Marcel Worring,et al.  Content-Based Image Retrieval at the End of the Early Years , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Ron Shonkwiler,et al.  An Image Algorithm for Computing the Hausdorff Distance Efficiently in Linear Time , 1989, Inf. Process. Lett..

[8]  Ming-Kuei Hu,et al.  Visual pattern recognition by moment invariants , 1962, IRE Trans. Inf. Theory.

[9]  Daniel P. Huttenlocher,et al.  Comparing Images Using the Hausdorff Distance , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Ruud M. Bolle,et al.  Feature based indexing for media tracking , 2000, 2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532).

[11]  Jordi Vitrià,et al.  Local Color Analysis for Scene Break Detection Applied to TV Commercials Recognition , 1999, VISUAL.