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Image spam filtering using Fourier-Mellin invariant features

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dc.contributor.authorZuo, H.
dc.contributor.authorLi, X.
dc.contributor.authorWu, O.
dc.contributor.authorHu, W.
dc.contributor.authorLuo, G.
dc.contributor.conferenceIEEE International Conference on Acoustics, Speech and Signal Processing (34th : 2009 : Taipei, Taiwan)
dc.date.issued2009
dc.description.abstractImage spam is a new obfuscating method which spammers invented to more effectively bypass conventional text based spam filters. In this paper, a framework for filtering image spams by using the Fourier-Mellin invariant features is described. Fourier-Mellin features are robust for most kinds of image spam variations. A one-class classifier, the support vector data description (SVDD), is exploited to model the boundary of image spam class in the feature space without using information of legitimate emails. Experimental results demonstrate that our framework is effective for fighting image spam.
dc.description.statementofresponsibilityHaiqiang Zuo, Xi Li, Ou Wu, Weiming Hu and Guan Luo
dc.identifier.citation2009 IEEE International Conference on Acoustics, Speech, and Signal Processing: Proceedings / pp.849-852
dc.identifier.doi10.1109/ICASSP.2009.4959717
dc.identifier.isbn9781424423545
dc.identifier.urihttp://hdl.handle.net/2440/67310
dc.language.isoen
dc.publisherIEEE
dc.publisher.placeOnline
dc.rights©2009 IEEE
dc.source.urihttp://dx.doi.org/10.1109/icassp.2009.4959717
dc.subjectImage spam
dc.subjectFourier-Mellin Transform
dc.subjectone-class classification
dc.titleImage spam filtering using Fourier-Mellin invariant features
dc.typeConference paper
pubs.publication-statusPublished

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