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Effective foreground detection under sudden illumination change is an active research topic. However, most existing background subtraction approaches, which are intensity based, fail to handle this situation. In this paper, we propose a novel background modeling method that overcomes this limitation by relying on statistical models which use pixel phase instead of intensities. We first extract the...
In this paper, a new technique based on Gabor filters with adaptive window is proposed for SAR image segmentation in overcomplete brushlet domain. SAR image is full of texture and direction information, and brushlet is a new kind of analysis tool for image with rich directional information. Aim at these characteristics, this paper combines Gabor filters with GLCP for segmentation in brushlet coefficients...
The usage of finger knuckle images for personal identification has shown promising results and generated lot of interest in biometrics. In this work, we investigate a new approach for efficient and effective personal identification using KnuckleCodes. The enhanced knuckle images are employed to generate KnuckleCodes using localized Radon transform that can efficiently characterize random curved lines...
This paper presents an effective algorithm of palmprint feature extraction. This algorithm is constructed on the basis of Gabor filter and moment invariant (MI). The process of implementing the algorithm is as follows: first, we perform wavelet transform of the original region of interest (ROI) of the palmprint image to get the approximation image (AIROI). Later, we exploit the Gabor filter to capture...
Gabor wavelet is a multi-resolution description. It could extract the gray feature of facial area using amplitude coefficients of Gabor wavelet even when illumination changes. Based on the fact, this paper proposes a face detection method employing BP network combined with Gabor wavelet transform. Sample features are represented by Gabor description for BP network training. First we use standard modules...
This paper present a multiresolution descriptors for fingerprint recognition .The first step in our method is compute the Discrete Fourier Transform (DFT) for the given fingerprint image then we transform it to polar coordinate (r,thetas ) using the centre of mass of the pattern as origin, then apply the Fourier transform along the axis of polar angle thetas and the wavelet transform along the axis...
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