@inproceedings{6ee1be51c4744291b329e640d7d3654d,
title = "A real-time matching system for large-small field of view images based on Zynq",
abstract = "Aiming at the requirement of real-time matching between the large field of view image of the night vision goggles on helmet and the small field of view image of the infrared rifle sight in the individual observation and sighting system, this paper uses the Zynq heterogeneous embedded platform and adopts the software and hardware co-design method to build a system that can match the two images in real time. Experiments show that when the large field of view image is 640×480 pixels, the small field of view image is 200×200 pixels, and the frame rate of the two cameras is 25 frames per second, this system{\textquoteright}s matching frame rate reaches 23 frames per second, which meets the needs of real-time matching. The system has a certain degree of robustness to rotation and zooming, and its matching accuracy is high.",
keywords = "Image matching, ORB, Real-time, Zynq",
author = "Zhiyu Fu and Li Li and Weiqi Jin and Hongchang Cheng",
note = "Publisher Copyright: {\textcopyright} 2021 SPIE.; 2021 International Conference on Laser, Optics and Optoelectronic Technology, LOPET 2021 ; Conference date: 28-05-2021 Through 30-05-2021",
year = "2021",
doi = "10.1117/12.2602292",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Changsi Peng and Fengjie Cen",
booktitle = "International Conference on Laser, Optics and Optoelectronic Technology, LOPET 2021",
address = "United States",
}
