Integrating neural networks and PCA for fast covert surveillance

Authors:
Hazem M. El-Bakry;Mamoon H. Mamoon
Affiliations:
Faculty of Computer Science & Information Systems, Mansoura University, Egypt;Faculty of Computer Science & Information Systems, Mansoura University, Egypt
Venue:
CI'10 Proceedings of the 4th WSEAS international conference on Computational intelligence
Year:
2010

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Abstract

In this paper, a fast algorithm for covert surveillance is presented. Such algorithm uses fast neural networks (FNNs) for human face detection. The proposed FNNs applies cross correlation in the frequency domain between the input image and the weights of neural networks. For the purpose of efficient observation and monitoring by higher administration, we need to transfer the detected face to higher administration. Therefore, efficient compression algorithm is needed. Here, the hybrid method k-PCA is used. It is proved mathematically and practically that the proposed combined algorithms are efficient for face detection and compression.