Discrete Orthognal Moment Features Using Chebyshev Polynomials

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dc.contributor.authorMukundan, R.
dc.contributor.authorOng, S.H.
dc.contributor.authorLee, P.A.
dc.date.accessioned2007-09-06T01:08:41Z
dc.date.available2007-09-06T01:08:41Z
dc.date.issued2000en
dc.description.abstractThis paper introduces a new set of moment functions based on Chebyshev polynomials which are orthogonal in the discrete domain of the image coordinate space. Chebyshev moments eliminate the problems associated with conventional orthogonal image moments such as the Legendre moments and the Zernike moments. The theoretical framework of discrete orthogonal moments is given, and their superior feature representation capability is demonstrated.en
dc.identifier.citationMukundan, R., Ong, S.H., Lee, P.A. (2000) Discrete Orthognal Moment Features Using Chebyshev Polynomials. New Zealand: International Conference on Image and Vision Computing - IVCNZ'00, 27-29, November 2000. 20--25.en
dc.identifier.isbn978-0-473-07213-1
dc.identifier.urihttp://hdl.handle.net/10092/446
dc.language.isoen
dc.publisherUniversity of Canterbury. Computer Science and Software Engineering.en
dc.rights.urihttps://hdl.handle.net/10092/17651en
dc.subjectpattern recognitionen
dc.subjectimage moment functionsen
dc.subjectorthogonal momentsen
dc.subjectchebyshev polynomialsen
dc.subject.marsdenFields of Research::280000 Information, Computing and Communication Sciences::280200 Artificial Intelligence and Signal and Image Processing::280207 Pattern recognitionen
dc.subject.marsdenFields of Research::280000 Information, Computing and Communication Sciences::280200 Artificial Intelligence and Signal and Image Processing::280203 Image processingen
dc.titleDiscrete Orthognal Moment Features Using Chebyshev Polynomialsen
dc.typeConference Contributions - Published
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