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Wavelet transform provides a sparse representation of a signal and it has been shown that it closely matches with the human perceptual system [1, 2]. This means that applying wavelet transform leads to a more accurate recognition of signals. In this paper, a robust face recognition system based on wavelet transform of the Scale Invariant Feature Transform (SIFT) features is introduced. Applying wavelet...
Current background subtraction methods require background modeling to handle dynamic backgrounds. The purpose of our study is to investigate a background template substraction method to detect foreground objects in the presence of background variations. The method uses a single reference image but the change detection process allows change in the background including illumination changes and dynamic...
This paper develops an approach to measure the information content of a biometric feature representation. We define biometric information as the decrease in uncertainty about the identity of a person due to a set of biometric measurements. We then show that the biometric feature information for a person may be calculated by the relative entropy $${D(p\|q)}$$ between the population feature distribution...
This paper addresses the issue of the information content of a biometric image or system. We define biometric information as the decrease in uncertainty about the identity of a person due to a set of biometric measurements. We then show that the biometric information for a person may be calculated by the relative entropy D(pparq) between the population feature distribution q and the person's feature...
This paper presents a method to improve face detection by locating eyes in an image using infrared (IR) light, based on reflections due to the red-eye effect. The developed method analyzes two consecutive frames where the first one is taken under regular illumination with no IR and the second one using IR. The location of the eyes and the face contour are computed from the IR images using a collection...
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