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Homomorphic Filtering and Phase-Based Matching for Cross-Spectral Cross-Distance Face Recognition.

Fitri Arnia^1,2, Maulisa Oktiana¹, Khairun Saddami¹

¹Department of Electrical and Computer Engineering, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia.

Sensors (Basel, Switzerland)

|July 20, 2021

Summary

This study introduces a novel phase-based approach for Cross-Spectral Cross Distance (CSCD) face recognition, improving security surveillance. The method achieves high accuracy in recognizing faces across different lighting and distances, outperforming existing CSCD techniques.

Keywords:

BLPOC cross-distance face recognition cross-spectral face recognition photometric normalization

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Area of Science:

Computer Vision and Pattern Recognition
Biometric Security Systems

Background:

Facial recognition is crucial for security and surveillance.
Recognizing faces at varying distances and lighting (day/night) remains a significant challenge.
Cross-Spectral Cross Distance (CSCD) face recognition addresses these difficulties.

Purpose of the Study:

To propose a novel phase-based approach for CSCD face recognition.
To evaluate the performance of the proposed method in challenging real-world scenarios.

Main Methods:

Utilized Homomorphic filtering for photometric normalization.
Employed Band Limited Phase Only Correlation (BLPOC) for robust image matching.
Directly used the phase component of images, bypassing traditional feature extraction.

Main Results:

The proposed phase-based CSCD method demonstrated superior recognition performance.
Achieved an Equal Error Rate (EER) of 5.34% and a Genuine Acceptance Rate (GAR) of 93%.
Outperformed baseline CSCD approaches in all tested cross-spectral and cross-distance scenarios.

Conclusions:

The phase-based CSCD face recognition approach is effective for challenging surveillance conditions.
The method offers a promising solution for enhancing security systems with robust facial recognition capabilities.