Automated User Identification from Facial Thermograms with Siamese Networks

• URL: http://arxiv.org/abs/2512.13361v1
• Date: Mon, 15 Dec 2025 14:13:49 GMT
• Title: Automated User Identification from Facial Thermograms with Siamese Networks
• Authors: Elizaveta Prozorova, Anton Konev, Vladimir Faerman,
• Abstract summary: The article analyzes the use of thermal imaging technologies for biometric identification based on facial thermograms.<n>Siamese neural networks are proposed as an effective approach for automating the identification process.<n>The results indicate that thermal imaging is a promising technology for developing reliable security systems.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: The article analyzes the use of thermal imaging technologies for biometric identification based on facial thermograms. It presents a comparative analysis of infrared spectral ranges (NIR, SWIR, MWIR, and LWIR). The paper also defines key requirements for thermal cameras used in biometric systems, including sensor resolution, thermal sensitivity, and a frame rate of at least 30 Hz. Siamese neural networks are proposed as an effective approach for automating the identification process. In experiments conducted on a proprietary dataset, the proposed method achieved an accuracy of approximately 80%. The study also examines the potential of hybrid systems that combine visible and infrared spectra to overcome the limitations of individual modalities. The results indicate that thermal imaging is a promising technology for developing reliable security systems.

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