Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/106237
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dc.contributor.authorLian, Zhichaoen
dc.contributor.authorEr, Meng Jooen
dc.date.accessioned2014-10-07T03:13:01Zen
dc.date.accessioned2019-12-06T22:07:07Z-
dc.date.available2014-10-07T03:13:01Zen
dc.date.available2019-12-06T22:07:07Z-
dc.date.copyright2012en
dc.date.issued2012en
dc.identifier.citationLian, Z., & Er, M. J. (2012). Local relation map : a novel illumination invariant face recognition approach. International journal of advanced robotic systems, 9, 128-.en
dc.identifier.issn1729-8806en
dc.identifier.urihttps://hdl.handle.net/10356/106237-
dc.description.abstractIn this paper, a novel illumination invariant face recognition approach is proposed. Different from most existing methods, an additive term as noise is considered in the face model under varying illuminations in addition to a multiplicative illumination term. High frequency coefficients of Discrete Cosine Transform (DCT) are discarded to eliminate the effect caused by noise. Based on the local characteristics of the human face, a simple but effective illumination invariant feature local relation map is proposed. Experimental results on the Yale B, Extended Yale B and CMU PIE demonstrate the outperformance and lower computational burden of the proposed method compared to other existing methods. The results also demonstrate the validity of the proposed face model and the assumption on noise.en
dc.language.isoenen
dc.relation.ispartofseriesInternational journal of advanced robotic systemsen
dc.rights© 2012 Zhichao et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en
dc.subjectDRNTU::Engineering::Systems engineeringen
dc.titleLocal relation map : a novel illumination invariant face recognition approachen
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.identifier.doi10.5772/51667en
dc.description.versionPublished versionen
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