Audio watermarking framework using multi-objective particle swarm optimization

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dc.contributor.authorPeng, H.
dc.contributor.authorZhang, Z.
dc.contributor.authorWang, J.
dc.contributor.authorShi, P.
dc.date.issued2013
dc.description.abstractAiming at the multi-objective essence of optimal audio watermarking problem, we propose a novel audio watermarking framework in this paper, which can optimally balance all conflicting objectives of the problem, fidelity and robustness against different attacks. In the proposed framework, a multi-objective particle swarm optimization technique based on fitness sharing is applied to search optimal watermarking parameters and Pareto-optimal solutions are used to express the optimal parameters found. In addition, the proposed framework has the following advantages: (i) it can avoid the difficulty of determining optimal weighted factors in the existing single-objective watermarking schemes; (ii) Pareto-optimal solutions can offer the flexibility to select optimal parameters for satisfying different application demands. © 2013 ICIC International.
dc.description.statementofresponsibilityHong Peng, Zulin Zhang, Jun Wang and Peng Shi
dc.identifier.citationInternational Journal of Innovative Computing Information and Control, 2013; 9(7):2789-2800
dc.identifier.issn1349-4198
dc.identifier.issn1349-418X
dc.identifier.orcidShi, P. [0000-0001-8218-586X] [0000-0002-0864-552X] [0000-0002-1358-2367] [0000-0002-5312-5435]
dc.identifier.urihttp://hdl.handle.net/2440/79927
dc.language.isoen
dc.publisherICIC International
dc.rights© 2013
dc.source.urihttp://www.ijicic.org/ijicic-12-04154.pdf
dc.subjectOptimal audio watermarking
dc.subjectAudio watermarking framework
dc.subjectMulti-objective optimization
dc.subjectParticle swarm optimization
dc.titleAudio watermarking framework using multi-objective particle swarm optimization
dc.typeJournal article
pubs.publication-statusPublished

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