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.

翻译：本文分析了利用热成像技术基于面部热成像图进行生物特征识别的应用。文章对红外光谱范围（近红外、短波红外、中波红外和长波红外）进行了比较分析。同时，论文明确了用于生物特征识别系统的热像仪的关键要求，包括传感器分辨率、热灵敏度以及至少30 Hz的帧率。研究提出采用孪生神经网络作为自动化识别过程的有效方法。在自有数据集上进行的实验中，所提方法达到了约80%的准确率。研究还探讨了结合可见光与红外光谱的混合系统在克服单一模态局限性方面的潜力。结果表明，热成像技术是开发可靠安全系统的一项前景广阔的技术。