Design and Implementation of an Online Voting System with Face Recognition

Secure online voting system using facial recognition to authenticate voters and prevent multiple voting.

About this project

This project develops a secure online voting platform that uses facial recognition (OpenCV / face-api.js) to verify voter identity at login and at the moment a vote is cast. It targets student union elections in Nigerian universities, eliminating ballot box snatching and double voting.

Suggested tech stack

Python / Django
OpenCV / face-api.js
PostgreSQL
Bootstrap

Chapters 1–5 outline

Chapter 1

Introduction: background to biometric online voting, statement of the problem (manual voting in Nigerian institutions suffers from impersonation, rigging, and slow result collation), aim and objectives, research questions, scope, significance of the study, and definition of terms.

Chapter 2

Literature Review: theoretical framework, review of related works on biometric online voting, gaps in existing studies, and a summary positioning this project.

Chapter 3

Methodology / System Analysis and Design: Python + Django + OpenCV for face recognition; PostgreSQL for vote storage; rapid application development. Includes data collection method, system requirements, use-case and architecture diagrams (or population, sample size, and instrument).

Chapter 4

Implementation and Results: a deployed web app that conducts an election end-to-end with real-time result tally. Presentation of findings, testing, evaluation, and discussion of results.

Chapter 5

Summary, Conclusion and Recommendations: key findings, contribution to knowledge, limitations, and recommendations for further research.

Get this project done — chapters, code, defence support

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