dc.contributor.authorLian, Zhichao
dc.contributor.authorEr, Meng Joo
dc.contributor.authorLi, Juekun
dc.description.abstractThis paper presents a novel illumination normalization method to address the issue of illumination invariant face recognition. The proposed method applies a Difference of Gaussians (DoG) filter in the logarithm domain of the images to reduce the effects caused by the shadows. After that, a local relation map (LRM) is extracted as illumination invariant features for further recognition task. The proposed method outperforms the existing normalization approaches significantly based on the experimental results in the Yale B and Extended Yale B database. Moreover, the proposed method does not involve any prior information or modeling step and takes a low computational loan. Therefore it can be easily implemented in a real-time face recognition system.en_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering
dc.titleA novel illumination normalization method based on local relation mapen_US
dc.typeConference Paper
dc.contributor.conferenceIEEE Conference on Industrial Electronics and Applications (7th : 2012 : Singapore)en_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US

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