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A novel hybrid approach based on Bayesian and wavelet transform for face recognition is proposed. Firstly the system uses PCA to select the first 10 candidate images, secondly these candidate images and each testing image are decomposed into low frequency and high frequency sub-band images by applying wavelet transform, Bayesian recognition is parallel processed using these sub-band images. The face...
A novel Bayesian approach to face recognition based on wavelet transform is proposed. The original image is decomposed into low frequency and high frequency sub-band images by applying wavelet transform, the 2DPCA algorithm is used to compute the eigenvector space of the face. Firstly Bayesian approach is used to the low frequency sub-band, select the top 10 candidate images for matching in the post...
Bayesian subspace analysis has been successfully applied in face recognition. However, the direct application of the algorithm is much more computationally intensive. In this paper, a novel Bayesian approach to face recognition based on 2DPCA is proposed. Firstly the system uses 2DPCA to select the 10 top-ranked candidate images, secondly these candidate images and each testing image are decomposed...
In this paper are presented the results of optimizing the combination of some common techniques and classifiers applied to faces recognition by the using of genetic algorithms, the set of images used for this approach comes from infrared acquisition. It appears that the proposed scheme improve the system performance compared to the single technique developments. This research opens a wide range of...
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