集成电路与嵌入式系统2024，Vol.24Issue(10)：19-24,6.DOI:10.20193/j.ices2097-4191.2024.0007
基于FPGA和BNN的高效车牌识别系统设计
Efficient license plate recognition system based on FPGA and BNN
袁敏 1张振东1
作者信息
- 1. 中国科学院大学人工智能学院,北京 100049
- 折叠
摘要
Abstract
To address the issues of slow processing speed,low accuracy,and high hardware resource consumption in traditional license plate recognition systems,an efficient license plate recognition system is designed and implemented.This system is based on Field-Pro-grammable Gate Array(FPGA)and Binary Neural Network(BNN)technology.By combining hardware acceleration with algorithm optimization,the system significantly enhances license plate recognition performance.The experimental results show that the system a-chieves a recognition accuracy of 96.46％,reducing the recognition time to 12 milliseconds.Compared to traditional license plate recog-nition algorithms and CNN-FPGA solutions,this system demonstrates significant advantages in hardware resource consumption,rec-ognition speed,and accuracy,providing an efficient and resource-friendly solution for license plate recognition.关键词
FPGA/BNN/车牌识别系统/硬件加速/算法优化Key words
FPGA/BNN/license plate recognition system/hardware acceleration/algorithm optimization分类
信息技术与安全科学引用本文复制引用
袁敏,张振东..基于FPGA和BNN的高效车牌识别系统设计[J].集成电路与嵌入式系统,2024,24(10):19-24,6.
