A Robust Perceptual Audio Hashing Using Balanced Multiwavelets

(2006) A Robust Perceptual Audio Hashing Using Balanced Multiwavelets. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2006, Toulouse, France.

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Digital multimedia content (especially audio) is becoming a major part of the average computer user experience. Large digital audio collections of music, audio and sound effects are also used by the entertainment, music, movie and animation industries. Therefore, the need for identification and management of audio content grows proportionally to the increasing widespread availability of such media virtually ”any time and any where” over the Internet. In this paper, we propose a novel framework for robust perceptual hashing of audio content using balanced multiwavelets (BMW). The framework for generating robust perceptual hash values (or fingerprints) is described. The generated hash values are used for identifying, searching, and retrieving audio content from large audio databases. Furthermore, we illustrate, through extensive computer simulation, the robustness of the proposed framework to efficiently represent audio content and withstand several signal processing attacks and manipulations.

Item Type: Conference or Workshop Item (Paper)
Subjects: Computer
Department: College of Computing and Mathematics > Information and Computer Science
Depositing User: LAHOUARI GHOUTI
Date Deposited: 18 Jun 2008 08:00
Last Modified: 01 Nov 2019 13:46
URI: http://eprints.kfupm.edu.sa/id/eprint/9154