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Title: Biometrics security and experiments on face recognition algorithms
Authors: Dandashi, Amal
Karam, Walid 
Affiliations: Department of Computer Engineering 
Keywords: Software tools
Bayes methods
Biometrics (access control)
Face recognition
Image classification
Security of data
Subjects: Principal component analysis
Issue Date: 2012
Publisher: IEEE
Part of: IEEE Symposium on Computational Intelligence for Security and Defence Applications
Conference: IEEE Symposium on Computational Intelligence for Security and Defence Applications (1-13 July 2012 : Ottawa, ON, Canada) 
Biometrics security analysis and performance evaluation of the following Face Recognition Algorithms is performed: Principal Components Analysis (PCA), Linear Discriminant Analysis (LDA) and Bayesian Intrapersonal/Extrapersonal Classifier (BIC), using the BANCA database. Software tools retrieve and preprocess images from sequential records within the BANCA database for algorithm evaluation. Then a verification environment over the set of images to be tested is developed, the above algorithms are invoked over the verification set, and verification parameters are collected. Results proved PCA performed most accurately and effectively with regards to security concerns, with an average recognition rate of 93%, while LDA and BIC lagged behind with recognition rates ranging from 80%-83%.
Ezproxy URL: Link to full text
Type: Conference Paper
Appears in Collections:Department of Computer Engineering

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