An Efficient Method for Face Recognition System In Various Assorted Conditions

TL;DR

This paper presents a face recognition system that combines preprocessing, Fourier-based feature extraction, and score fusion, demonstrating robustness under various lighting and location conditions with an 88.1% verification rate.

Contribution

It introduces a hybrid Fourier-based feature extraction method and a score fusion scheme to improve face recognition under diverse lighting conditions.

Findings

Achieved 88.1% verification rate across different lighting conditions.

Effective face recognition in indoor and outdoor environments.

Enhanced robustness to lighting variations.

Abstract

In the beginning stage, face verification is done using easy method of geometric algorithm models, but the verification route has now developed into a scientific progress of complicated geometric representation and identical procedure. In recent years the technologies have boosted face recognition system into the healthy focus. Researchers currently undergoing strong research on finding face recognition system for wider area information taken under hysterical elucidation dissimilarity. The proposed face recognition system consists of a narrative expositionindiscreet preprocessing method, a hybrid Fourier-based facial feature extraction and a score fusion scheme. We have verified the face recognition in different lightening conditions (day or night) and at different locations (indoor or outdoor). Preprocessing, Image detection, Feature- extraction and Face recognition are the methods used for face verification system. This paper focuses mainly on the issue of toughness to lighting variations. The proposed system has obtained an average of 88.1% verification rate on Two-Dimensional images under different lightening conditions.