A Novel Hybrid Biometric Electronic Voting System: Integrating Finger Print and Face Recognition
Shahram Najam Syed, Aamir Zeb Shaikh, Shabbar Naqvi

TL;DR
This paper presents a hybrid biometric electronic voting system combining fingerprint and facial recognition to improve accuracy and security, utilizing machine learning classifiers and achieving 91% facial recognition accuracy under nominal lighting conditions.
Contribution
It introduces a novel hybrid biometric voting system integrating face and fingerprint recognition with cascaded classifiers for enhanced accuracy and reliability in election verification.
Findings
Achieves 91% facial recognition accuracy under nominal lighting.
Performs better than single biometric schemes or other classifiers.
Provides a more secure and accurate voting verification method.
Abstract
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…
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Taxonomy
TopicsAdvanced Steganography and Watermarking Techniques · Internet Traffic Analysis and Secure E-voting · Biometric Identification and Security
