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)


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.


Face Recognition False Acceptance Rate False Rejection Rate Face Recognition Method IEEE Signal Processing Society 
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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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