现代信息科技2024，Vol.8Issue(24)：40-43,4.DOI:10.19850/j.cnki.2096-4706.2024.24.009
基于YOLOv3的图像特征融合的车辆再识别算法研究
Research on Vehicle Re-recognition Algorithm of Image Feature Fusion Based on YOLOv3
摘要
Abstract
In order to improve the accuracy of vehicle re-recognition,a method combining global and local features is proposed,which solves the problem of low license plate recognition accuracy caused by factors such as blurred license plates,unclear vehicle contours,and occlusion during vehicle re-recognition.Firstly,this paper uses Siamese Network to match the rear shape,front appearance,and overall vehicle shape of the vehicle images to be detected.Then,it uses the LPRNet based on YOLOv3 to combine the vehicle local shape,overall shape,and license plate recognition for vehicle re-recognition.The results show that the proposed method can achieve vehicle re-recognition under the changeable road environment,and the comprehensive accuracy of re-recognition reaches 93.63%,which is 7.28%,3.08%and 0.75%higher than the re-recognition model of DRDL,OIFE and RAM,respectively.关键词
人工智能/深度学习/车辆再识别Key words
Artificial Intelligence/Deep Learning/vehicle re-recognition分类
信息技术与安全科学引用本文复制引用
刘艳洋,闫昊..基于YOLOv3的图像特征融合的车辆再识别算法研究[J].现代信息科技,2024,8(24):40-43,4.基金项目
张家口市2024年度社会科学规划课题(2024055) （2024055）
