Image Processing Technique for Field of View Measurement of Electro-Optical Imaging System

Khare, Sudhir; Singh, Manvendra K.; Kaushik, Brajesh Kumar; Chandra, Kanchan

doi:10.1007/978-981-15-9259-1_84

Springer Proceedings in Physics

2021

DOI: 10.1007/978-981-15-9259-1_84

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Image Processing Technique for Field of View Measurement of Electro-Optical Imaging System

Sudhir Khare

Manvendra K. Singh

Brajesh Kumar Kaushik

et al.

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2024

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“…The system's experimental results demonstrate potential applications in physical measurements, with disparity decreasing as the object moves away from the camera(Ristanto et al, 2021). Sudhir Khare et al introduced a study focusing on the development of an image processing technique for measuring the field of view of electro-optical imaging systems, aiming to enhance precision and efficiency through a user-friendly graphics user interface approach(Khare et al, 2021).…”

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

Elri,

Ergüzen

2024

JCEEES

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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.

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

Elri,

Ergüzen

2024

JCEEES

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Image Processing Technique for Field of View Measurement of Electro-Optical Imaging System

Cited by 1 publication

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

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

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