Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
Discriminant Analysis of Principal Components for Face Recognition
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
A PDA-based Face Recognition System
WACV '02 Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision
Journal of Cognitive Neuroscience
Face recognition using fuzzy Integral and wavelet decomposition method
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A personal identity annotation overlay system using a wearable computer for augmented reality
IEEE Transactions on Consumer Electronics
Hi-index | 0.00 |
In this paper, we propose a secure authentication method based on multimodal biometrics system under ubiquitous computing environments. For this, the face and signature images are acquired in PDA and then each image with user ID and name is transmitted via WLAN (Wireless LAN) to the server and finally the PDA receives authentication result from the server. In the proposed system, face recognition algorithm is designed by PCA and LDA. On the other hand, the signature verification is designed by a novel method based on grid partition, Kernel PCA and LDA. To calculate the similarity between test image and training image, we adopt the selective distance measure determined by various experiments. More specifically, Mahalanobis and Euclidian distance measures are used for face and signature, respectively. As the fusion step, decision rule by weighted sum fusion scheme effectively combines the two matching scores calculated in each biometric system. From the real-time experiments, we convinced that the proposed system makes it possible to improve the security as well as user's convenience under ubiquitous computing environments.