Vehicle LED detection and segmentation recognition based on deep learning for optical camera communication

被引：0
|
作者：
CHENG Qing [1 ]
MA Haitao [1 ]
SUN Xu [1 ]
机构：
[1] Department of Communications Engineering, Jilin University
来源：
OptoelectronicsLetters | 2022年 / 18卷 / 08期
关键词：
D O I：
暂无
中图分类号：
U495 [电子计算机在公路运输和公路工程中的应用]; TN929.5 [移动通信]; TP391.41 [];
学科分类号：
080203 ; 080402 ; 080904 ; 0810 ; 081001 ; 0838 ;
摘要：
In the vehicle to vehicle(V2V) communication based on optical camera communication(OCC) system, how to achieve high reliability and low latency communication is still a problem. In this paper, we propose a lightweight light-emitting diode(LED) detection algorithm based on deep learning to detect the vehicle LED position at different communication distances, which can improve LED detection accuracy and inference speed. In addition, we design an LED segmentation recognition algorithm to reduce the bit error rate(BER) of the vehicle OCC system. The experimental results demonstrate the effectiveness of the proposed algorithms in real traffic scenes.
引用
收藏
页码：508 / 512
页数：5
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