桂林电子科技大学学报2025，Vol.45Issue(1)：54-61,8.DOI:10.16725/j.1673-808X.2022334
基于YOLOv5和视频防抖的船只检测系统
Vessel inspection system based on YOLOv5 and video stabilization
摘要
Abstract
A ship detection system based on YOLOv5 and video stabilization is designed and implemented to effectively solve the problems of inflexible deployment,insufficient detection accuracy,and poor real-time performance in traditional sea surface detec-tion solutions.The system consists of a front-end user operation module,a back-end service module,and a sea target detection mod-ule,and is deployed on the Jetson AGX hardware platform.The system is designed and implemented in detail,and after integrating the YOLOv5 object detection algorithm and digital video stabilization algorithm,it can accurately identify and remotely monitor sea targets using edge-based unmanned ship-mounted devices,and provide remote control functions.Through experiments,the system has good ship recognition performance,and after optimizing the captured video with stabilization,the recognition accuracy under windy and wavy conditions can be significantly improved.At the same time,according to on-site actual test results,the system pro-vides users with centralized control and management functions through an integrated operation platform,and can achieve a video frame rate of 45 frame/s and a playback delay of less than 2 s,meeting real-time requirements.关键词
船只检测/远程控制/硬件部署/设计与实现/神经网络/视频防抖Key words
vessel inspection/remote control/hardware deployment/design and implementation/neural networks/video stabiliza-tion分类
信息技术与安全科学引用本文复制引用
蔡颂,刘庆华,叶金才..基于YOLOv5和视频防抖的船只检测系统[J].桂林电子科技大学学报,2025,45(1):54-61,8.基金项目
广西创新驱动发展专项(桂科AA21077008) （桂科AA21077008）
桂林市重点研发计划(2020010305) （2020010305）
