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This paper presents a novel scheme for feature extraction for face recognition by fusing local and global discriminant features. The facial changes due to variations of pose, illumination, expression, etc. are often appeared only some regions of the whole face image. Therefore, global features extracted from the whole image fail to cope with these variations. To address these problems, face images...
An automated algorithm to localize irises for Middle East individuals had been developed in this research. Histogram equalization, Logabout, Difference of Gaussian (DoG), wavelet transformation, Principle Component Analysis (PCA) and Artificial Neural Network are popular techniques used for image processing, feature extraction and classification. A fusion of these techniques had been introduced to...
We present a study on different levels of visible and infrared modalities fusion for face recognition. While visible modality is the most natural way to recognize someone, infrared presents thermal distribution that can be useful for face recognition. We compare the well-known eigenfaces method as a baseline to an approach based on sparsity for the feature extraction and the classification. Applied...
Patch-based face recognition is a recent method which uses the idea of analyzing face images locally, in order to reduce the effects of illumination changes and partial occlusions. Feature fusion and decision fusion are two distinct ways to make use of the extracted local features. Apart from the well-known decision fusion methods, a novel approach for calculating weights for the weighted sum rule...
Making recognition more reliable under uncontrolled lighting conditions is one of the most important challenges for practical face recognition systems. We tackle this by combining the strengths of robust illumination normalization, local texture-based face representations, distance transform based matching, kernel-based feature extraction and multiple feature fusion. Specifically, we make three main...
A face recognition method based on fuzzy data fusion is presented. In traditional principle component analysis method, operating directly on the whole face image leads to only global information about face image can be extracted and local one may be neglected. It is not very effective under variations of facial expression, pose and illumination. To solve this problem, in proposed scheme, each original...
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