PCA based Multimodal Biometrics using Ear and Face Modalities
Автор: Snehlata Barde, A S Zadgaonkar, G R Sinha
Журнал: International Journal of Information Technology and Computer Science(IJITCS) @ijitcs
Статья в выпуске: 5 Vol. 6, 2014 года.
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Automatic person identification is an important task in computer vision and related applications. Multimodal biometrics involves more than two modalities. The proposed work is an implementation of person identification fusing face and ear biometric modalities. We have used PCA based neural network classifier for feature extraction from the images. These features are fused and used for identification. PCA method was found better if the modalities were combined. Identification was made using Eigen faces, Eigen ears and their features. These were tested over own created database.
Biometrics, Principal Component Analysis (PCA), Eigen Faces, Eigen Ears, Euclidian Distance Hierarchical Matching, Calligraphic Retrieval, Skeleton Similarity
Короткий адрес: https://sciup.org/15012080
IDR: 15012080
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