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The present article focuses on the classification of fingerprints. Our aim goal is to unify the process of fingerprint compression, classification and identification. The well known methods suited to these tasks are based on WSQ (Wavelet Scalar Quantization) for compression, Gabor filters for classification and minutiae matching for identification. We propose to use Block Ridgelet Transform (BRT)...
A new classification method called affine subspace nearest points (ASNP) algorithm is presented in this paper. Similar to the idea of the geometrical explanation of support vector machines (SVMs), the ASNP algorithm designed by us as a binary classifier extends the areas searched for the nearest points from the convex hulls in SVM to affine subspaces, and constructs the decision hyperplane separating...
In this paper, we present a face recognition method based on the combination of the LoG-Gabor wavelets (GW) and the phase congruency (PC) method. The phase congruency feature images were obtained by applying phase congruency model to these multi-view face images with log-Gabor wavelets filters over 5 scales and 8 orientations, and then the mean and standard deviation of the image output are computed...
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