Face Recognition with Weightless Neural Networks Using the MIT Database

  • K. Khaki
  • T. J. Stonham
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7326)

Abstract

In this paper we propose a new face recognition method based on the weightless neural network system [1]. The algorithm uses 5-pixel n-tuples to map images, which passes through a ranking transform to obtain a binary n-tuple state. A digital neural network correlates the recurring states obtained from the current input pattern to those extracted from the test set. The data used in this paper is from the MIT-CBCL facial database [2], and the training data and testing data set each consist of 10 individual persons, with 100 examples of each subject. An error rate of 0.1% FAR and 0.1% FRR was achieved on data which was totally independent of the training set.

Keywords

Face Recognition False Acceptance Rate False Rejection Rate Face Recognition Method IEEE Signal Processing Society 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    Nazeer, S.A., Omar, N., Khalid, M.: Face Recognition using Artificial Neural Networks Approach. In: ICSCN 2007, pp. 420–425. MIT Campus, Anna University (2007)Google Scholar
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    Bojkovic, Z., Samcovic, A.: Face Detection Approach In Neural Network Based Method For Video Surveillance. In: NEUREL 2006. IEEE (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • K. Khaki
    • 1
  • T. J. Stonham
    • 1
  1. 1.Engineering DepartmentBrunel UniversityUxbridgeUK

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