Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Wireless integrated network sensors
Communications of the ACM
Fractional-Step Dimensionality Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Connecting the Physical World with Pervasive Networks
IEEE Pervasive Computing
Information fusion in biometrics
Pattern Recognition Letters - Special issue: Audio- and video-based biometric person authentication (AVBPA 2001)
Energy-Efficient Maximum Lifetime Algorithm in Wireless Sensor Networks
ICICTA '08 Proceedings of the 2008 International Conference on Intelligent Computation Technology and Automation - Volume 02
Bimodal personal recognition using hand images
Proceedings of the International Conference on Advances in Computing, Communication and Control
Face Recognition using Layered Linear Discriminant Analysis and Small Subspace
CIT '10 Proceedings of the 2010 10th IEEE International Conference on Computer and Information Technology
Bio-inspired Hybrid Face Recognition System for Small Sample Size and Large Dataset
IIH-MSP '10 Proceedings of the 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing
Biometrics: a tool for information security
IEEE Transactions on Information Forensics and Security
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Face recognition enhances the security through wireless sensor network and it is a challenging task due to constrains involved in wireless sensor network. Image processing and image communication in wireless sensor network reduces the life time of network due to the heavy processing and communication. This paper presents a collaborative face recognition system in wireless sensor network. The layered linear discriminant analysis is re-engineered to implement on wireless sensor network by efficiently allocating the network resources. Distributed face recognition not only help to reduce the communication overload but it also increase the node life time by distributing the work load on the nodes. The simulation shows that the proposed technique provide significant gain in network life time.