Please use this identifier to cite or link to this item:
|Title:||Biometrics security and experiments on face recognition algorithms||Authors:||Dandashi, Amal
|Affiliations:||Department of Computer Engineering||Keywords:||Software tools
Biometrics (access control)
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)||Abstract:||
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%.
|URI:||https://scholarhub.balamand.edu.lb/handle/uob/418||Ezproxy URL:||Link to full text||Type:||Conference Paper|
|Appears in Collections:||Department of Computer Engineering|
Show full item record
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.