THERMAL INFRARED OBJECT DETECTION WITH YOLO MODELS
Turmaganbet U. Zhexebay D. Turlykozhayeva D. Skabylov A. Akhtanov S. Temesheva S. Masalim P. Tao M.
2025E.A. Buketov Karaganda University Publish house
Eurasian Physical Technical Journal
2025#22Issue 2-52121 - 132 pp.
Object detection is a fundamental task in computer vision and remote sensing, aimed at recognizing and categorizing different types of objects within images. Unmanned aerial vehicle - based thermal infrared remote sensing provides crucial multi-scenario images and videos, serving as key data sources in public applications. However, object detection in these images remains challenging due to complex scene information, lower resolution compared to visible-spectrum videos, and a shortage of publicly available labeled datasets and trained models. This article introduces a Unmanned aerial vehicle - based thermal infrared object detection framework for analyzing images and videos in public applications and evaluates the performance of YOLOv8n/v8s, YOLOv11n/v11s, and YOLOv12n/v12s models in extracting features from ground-based thermal infrared images and videos captured by Forward-Looking Infrared cameras, as well as from unmanned aerial vehicle - recorded thermal infrared videos taken from various angles. The YOLOv8n/v8s, YOLOv11n/v11s, and the latest YOLOv12n/v12s models were deployed on a Raspberry Pi 5 using the OpenVINO framework. The successful deployment of these models, including the most recent version, demonstrates their feasibility for unmanned aerial vehicle-based thermal infrared object detection. The results show that YOLOv8 and YOLOv11 achieved high accuracy and recall rates of 93% and 92%, respectively, while the YOLOv12 model demonstrated good precision but comparatively lower performance in accuracy and recall, suggesting the possibility for further improvement.
Forward-Looking Infrared cameras , object detection , Raspberry Pi 5 , thermal infrared images , Unmanned aerial vehicle , YOLO models
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al-Farabi Kazakh National University, Almaty, Kazakhstan
Unmanned Aerial Vehicle Laboratory, Scientific Research Institute of Experimental and Theoretical Physics, Almaty, Kazakhstan
School of Electronics and Information, Northwestern Polytechnical University, Xian, China
al-Farabi Kazakh National University
Unmanned Aerial Vehicle Laboratory
School of Electronics and Information
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