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Fusion different biometrics is an effective way to design a biometric system with robust performance. To do this, normalization functions are employed. However, these functions can not follow the distributions of scores from distinct classifiers. Consequently different normalization errors are introduced. In this paper, the scores from different classifiers(More)
In this paper, we propose a novel matching score normalization method for multi-classifiers based on their false acceptance rate (FAR) scores to make fusion operable at the matching level. The classifier discriminant analysis (CDA) is put forward and implemented to single out the best score from the appreciate classifier as the fusion output. Experimental(More)
This paper introduces Gaborface-based 2DPCA and (2D)<sup>2</sup>PCA classification method based on 2D Gaborface matrices rather than transformed ID feature vectors. Two kinds of strategies to use the bank of Gaborfaces are proposed: ensemble Gaborface representation (EGFR) and multichannel Gaborface representation (MGFR). The feasibility of our method is(More)
Radical Basis Function (RBF) networks have been widely used in time series prediction because of their simplicity, robustness, good approximation and generalization ability. However, it is still rather difficult to select the number and locations of the hidden units of the RBF network appropriately for a specific time series prediction problem. In this(More)
Face recognition is an advanced identification solution which can meet the crying needs in security areas. Pose effect is a big challenge for robust applications of this technology. We proposed a feature transformation approach to cope with the head rotation roughly within half profile view. Comparing with algorithms based on computer vision technology, the(More)
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