Advancing defense capabilities through integration of electro-optical systems and computer vision technologies

Abstract

This paper presents a comprehensive study on the integration of cutting-edge technologies to enhance defense capabilities, focusing on object detection, tracking, and distance measurement tasks. Also, the integration of IMX219-77 cameras and Nvidia Jetson Nano for object detection, tracking, and distance measurement in electro-optical systems is proposed. The decision to combine these components was based on their individual strengths: the high resolution and wide field of view of the IMX219-77 cameras, and the low-power, high-performance capabilities of the Jetson Nano. Software-wise, OpenCV and GStreamer were chosen for their widespread use and capabilities in computer vision and multimedia processing tasks, respectively. The MOSSE algorithm was selected for object tracking due to its speed, efficiency, and resilience to lighting changes. Additionally, Depth Estimation (Stereo Vision) was employed for distance measurement by analyzing images captured from a pair of cameras. The proposed algorithm involves transmitting images from the cameras to the Jetson Nano, where OpenCV and GStreamer are utilized to process the data. The MOSSE algorithm is employed for object detection and tracking, while Depth Estimation generates depth maps to measure distances between objects and the camera. The study's results demonstrate accurate distance measurements with a margin of error ranging from 0 to 2 mm, falling below the acceptable threshold mentioned in academic literature. This aligns with similar studies in the field, showcasing the efficacy of the proposed integration for object detection, tracking, and distance measurement in electro-optical systems.