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In this paper, a new technique for constructing feature vector from DCT coefficients for gender classification has been presented. Firstly, images are divided into 8 × 8 sub images. DCT coefficients are calculated for each block in image. New technique is used for constructing the feature vector from DCT coefficients. Finally, SVM with Rbf kernel is used for classifying the images into male and female...
In this paper, we investigate the face recognition problem via clustering of frontal face images represented in frequency domain by low frequency discrete cosine transform (DCT) coefficients. Our approach termed as class specific space model (CSSM) is based on the assumption that faces of different subjects are clustered in different low dimensional subspace of the feature space. The proposed approach...
A nonlinear DCT discriminant feature extraction approach for face recognition is proposed. First, we analyze the nonlinear discriminabilities of DCT frequency bands and select appropriate bands. Second, we extract nonlinear discriminant features from the selected DCT bands by presenting a new kernel discriminant method, i.e. generalized kernel discriminative common vector (KDCV) method. The experimental...
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