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In many computer vision systems, one object can be described by multi-view data. Compared with individual view, multi-view data can contain complete and complementary information of the problem. But when views capture information which is uniquely but not complete enough to give an uniform learning performance, multi-view data may degrade the learning performance and it is therefore not an ideal solution...
In this paper, we focus on developing a novel noise-robust LBP-based texture feature extraction scheme for texture classification. Specifically, two solutions have been proposed to overcome the primary two reasons that cause local binary pattern sensitive to noise. First, a hybrid model is proposed for noise-robust texture description. In this new model, the local primitive micro features are encoded...
This paper proposes a new feature of fingerprint, called corner-cue. It is based on the curvature of fingerprint ridges. To extract the corner-cue, we first compute the curvature of fingerprint ridges and find the local maximum curvature points. Without regard to the high curvature points near minutiae, corner-cues are obtained. Corner-cues are further utilized in the matching stage to enhance the...
In this paper, we present an approach for writer identification using off-line Arabic handwriting. The proposed method introduced Arabic writing in a new form, by presenting Arabic writing in its basic components instead of alphabetic. We split the input document into two parts: one for the letters and the other for the diacritics, we extract all diacritics from the input image and calculate the LBP...
Face recognition has been studied extensively recently. The main difficulty faced by the current face recognition techniques stems from large variations in facial expression, pose and illumination. This paper presents an effective method for face recognition using nonseparable wavelet domain block-based PCA(BPCA) method. Our investigations demonstrate that the constructed nonseparable wavelet can...
This paper focuses on the rotation noise of iris recognition. Current iris recognition systems are unable to deal with the rotation noise perfectly. We propose a novel method for iris matching that decompose iris picture into wavelet subband coefficients via 16 non-separable wavelet filters, and use generalized Gaussian density (GGD) modeling of each non-separable orthogonal wavelet coefficients as...
This paper makes an attempt to analyze the local feature structure of iris texture information based on the barycenter distance of new non-separable wavelet. When preprocessed, the annular iris is normalized into a rectangular block. Several non-separable wavelet filters are used to capture the iris texture. In every filtered subband coefficients, we extract a certain number of largest positive coefficients...
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