Abstract
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.
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Lee, DJ., Kwon, MJ., Chun, MG. (2006). Secure Personnel Authentication Based on Multi-modal Biometrics Under Ubiquitous Environments. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4233. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893257_12
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DOI: https://doi.org/10.1007/11893257_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46481-5
Online ISBN: 978-3-540-46482-2
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