KEYWORDS: Feature extraction, Distance measurement, Binary data, Detection and tracking algorithms, Image processing, Databases, Signal to noise ratio, Information security, Biometrics, Digital watermarking
This paper discusses one of the important issues in generating a robust media hash. Robustness of a media
hashing algorithm is primarily determined by three factors, (1) robustness-false alarm tradeoff achieved by the
chosen feature representation, (2) accuracy of the bit extraction step and (3) the distance measure used to measure
similarity (dissimilarity) between two hashes. The robustness-false alarm tradeoff in feature space is measured
by a similarity (dissimilarity) measure and it defines a limit on the performance of the hashing algorithm. The
distance measure used to compute the distance between the hashes determines how far this tradeoff in the
feature space is preserved through the bit extraction step. Hence the bit extraction step is crucial, in defining
the robustness of a hashing algorithm. Although this is recognized as an important requirement by all, to our
knowledge there is no work in the existing literature that elucidates the effcacy of their algorithm based on their
effectiveness in improving this tradeoff compared to other methods. This paper specifically demonstrates the
kind of robustness false alarm tradeoff achieved by existing methods and proposes a method for hashing that
clearly improves this tradeoff.
Conference Committee Involvement (2)
Security, Forensics, Steganography, and Watermarking of Multimedia Contents X
28 January 2008 | San Jose, California, United States
Security, Steganography, and Watermarking of Multimedia Contents IX
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