Liew Yee Ping

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Face recognitions systems suffer from the problem associated with illumination variation. Therefore, there's a need to address this problem. In this paper, we present a novel algorithm for illumination normalization call Local Trapezoid Feature LTF. The features are derived from the trapezoid rule and the experiments results on extended Yale face database(More)
A regularized Independent Component Analysis (denoted as RICA) is proposed in the application of face verification. In RICA, information of correlation coefficients between images is employed to form a Laplacian matrix. This Laplacian matrix is used for locating localized features through regularizing the facial data before independent component analysis(More)
Discriminant Common Vectors (DCV) is proposed to solve small sample size problem. Face recognition encounters this dilemma where number of training samples is always smaller than the data dimension. In literature, it is shown that DCV is efficient in face recognition. In this paper, DCV is enhanced for further boosting its discriminating power. This(More)
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