August 11, 2025Journal of Engineering Research and ReportsOpen Access

A Biometric Voting Solution: Integrating Face Recognition with Embedded Systems for Secure Offline Elections

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The system achieved a recognition accuracy of 94.6%, with a face detection rate of 98.1%, indicating its reliability.
During voting, a live facial scan matches stored dataset images to ensure voter authenticity, granting access to vote.
Developed using Python and OpenCV, the face recognition feature employs the Local Binary Pattern Histogram method for efficiency.
This practical solution targets rural areas, ensuring elections can be transparent and secure without continuous internet connectivity.

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Implication

This system integrates face recognition and embedded systems to support secure offline elections, highlighting voter authenticity and protection against fraud.

Cite This Study

Apurbo et al. (2025) studied this question.

synapsesocial.com/papers/68a360ce0a429f7973328a88 https://doi.org/10.9734/jerr/2025/v27i71580

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Implication

This system integrates face recognition and embedded systems to support secure offline elections, highlighting voter authenticity and protection against fraud.

A Biometric Voting Solution: Integrating Face Recognition with Embedded Systems for Secure Offline Elections

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A Biometric Voting Solution: Integrating Face Recognition with Embedded Systems for Secure Offline Elections

Key Points

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Implication

Cite This Study

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