A Novel Hybrid Biometric Electronic Voting System: Integrating Finger Print and Face Recognition

A novel hybrid design based electronic voting system is proposed, implemented and analyzed. The proposed system uses two voter verification techniques to give better results in comparison to single identification based systems. Finger print and facial recognition based methods are used for voter ide...

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Main Authors: Shahram Najam, Aamir zeb Shaikh, Shabbar Naqvi
Format: Article
Language:English
Published: Mehran University of Engineering and Technology 2018-01-01
Series:Mehran University Research Journal of Engineering and Technology
Online Access:http://publications.muet.edu.pk/index.php/muetrj/article/view/100
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spelling doaj-224c509174a447109744e79fa6e290082020-11-24T23:37:49ZengMehran University of Engineering and TechnologyMehran University Research Journal of Engineering and Technology0254-78212413-72192018-01-01371100A Novel Hybrid Biometric Electronic Voting System: Integrating Finger Print and Face RecognitionShahram Najam0Aamir zeb Shaikh1Shabbar Naqvi2Department of Electronic Engineering, NED University of Engineering and Technology, KarachiDepartment of Electronic Engineering, NED University of Engineering and Technology, KarachiDepartment of Computer Systems Engineering, Baluchistan University of Engineering and Technology, KhuzdarA novel hybrid design based electronic voting system is proposed, implemented and analyzed. The proposed system uses two voter verification techniques to give better results in comparison to single identification based systems. Finger print and facial recognition based methods are used for voter identification. Cross verification of a voter during an election process provides better accuracy than single parameter identification method. The facial recognition system uses Viola-Jones algorithm along with rectangular Haar feature selection method for detection and extraction of features to develop a biometric template and for feature extraction during the voting process. Cascaded machine learning based classifiers are used for comparing the features for identity verification using GPCA (Generalized Principle Component Analysis) and K-NN (K-Nearest Neighbor). It is accomplished through comparing the Eigen-vectors of the extracted features with the biometric template pre-stored in the election regulatory body database. The results of the proposed system show that the proposed cascaded design based system performs better than the systems using other classifiers or separate schemes i.e. facial or finger print based schemes. The proposed system will be highly useful for real time applications due to the reason that it has 91% accuracy under nominal light in terms of facial recognition.http://publications.muet.edu.pk/index.php/muetrj/article/view/100
collection DOAJ
language English
format Article
sources DOAJ
author Shahram Najam
Aamir zeb Shaikh
Shabbar Naqvi
spellingShingle Shahram Najam
Aamir zeb Shaikh
Shabbar Naqvi
A Novel Hybrid Biometric Electronic Voting System: Integrating Finger Print and Face Recognition
Mehran University Research Journal of Engineering and Technology
author_facet Shahram Najam
Aamir zeb Shaikh
Shabbar Naqvi
author_sort Shahram Najam
title A Novel Hybrid Biometric Electronic Voting System: Integrating Finger Print and Face Recognition
title_short A Novel Hybrid Biometric Electronic Voting System: Integrating Finger Print and Face Recognition
title_full A Novel Hybrid Biometric Electronic Voting System: Integrating Finger Print and Face Recognition
title_fullStr A Novel Hybrid Biometric Electronic Voting System: Integrating Finger Print and Face Recognition
title_full_unstemmed A Novel Hybrid Biometric Electronic Voting System: Integrating Finger Print and Face Recognition
title_sort novel hybrid biometric electronic voting system: integrating finger print and face recognition
publisher Mehran University of Engineering and Technology
series Mehran University Research Journal of Engineering and Technology
issn 0254-7821
2413-7219
publishDate 2018-01-01
description A novel hybrid design based electronic voting system is proposed, implemented and analyzed. The proposed system uses two voter verification techniques to give better results in comparison to single identification based systems. Finger print and facial recognition based methods are used for voter identification. Cross verification of a voter during an election process provides better accuracy than single parameter identification method. The facial recognition system uses Viola-Jones algorithm along with rectangular Haar feature selection method for detection and extraction of features to develop a biometric template and for feature extraction during the voting process. Cascaded machine learning based classifiers are used for comparing the features for identity verification using GPCA (Generalized Principle Component Analysis) and K-NN (K-Nearest Neighbor). It is accomplished through comparing the Eigen-vectors of the extracted features with the biometric template pre-stored in the election regulatory body database. The results of the proposed system show that the proposed cascaded design based system performs better than the systems using other classifiers or separate schemes i.e. facial or finger print based schemes. The proposed system will be highly useful for real time applications due to the reason that it has 91% accuracy under nominal light in terms of facial recognition.
url http://publications.muet.edu.pk/index.php/muetrj/article/view/100
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