基于图像识别技术的高速公路实时监测与预警系统研究
Research on Highway Real-time Monitoring and Early Warning System Based on Image Recognition Technology
付毅恒1
作者信息
- 1. 广东省路桥建设发展有限公司,广东 广州 510663
- 折叠
摘要
为了解决高速公路监控人员手工巡检工作量大、效率低、准确性低的实际痛点,采用图像自动识别技术,以视频信号采集为起点,通过图像预处理、特征提取、目标识别与跟踪、异常事件检测、自动预警与处置的工作流程,建立YOLOv5 目标检测及DeepSORT目标根据算法,实时自动发现高速中出现的异常事件并及时预警处置,研究成果经过实际工程应用,验证了技术的创新性及可行性,可大大提高高速公路运营管理效率.
Abstract
In order to solve the actual pain points of large workload,low efficiency and low accuracy of manual inspection of monitoring personnel,the automatic image recognition technology is adopted,starting from video signal acquisition,and through image preprocessing,feature extraction,target recognition and tracking,abnormal event detection,automatic early warning and disposal and so on,the abnormal events in the highway are automatically discovered in real time and timely early warning and disposal.Through the practical engineering application,the innovation and feasibility of the research results are verified,and the technology greatly improves the efficiency of the highway operation and management.
关键词
YOLOv5目标检测/DeepSORT目标跟踪/特征提取/事件检测/机器深度学习Key words
YOLOv5 object detection/DeepSORT target tracking/feature extraction/event detection/machine Deep Learning引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据