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

Qing Cheng, Haitao Ma, Xu Sun

Optoelectronics Letters ›› 2022, Vol. 18 ›› Issue (8) : 508-512.

Optoelectronics Letters ›› 2022, Vol. 18 ›› Issue (8) : 508-512. DOI: 10.1007/s11801-022-2026-5
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Vehicle LED detection and segmentation recognition based on deep learning for optical camera communication

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Abstract

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.

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Qing Cheng, Haitao Ma, Xu Sun. Vehicle LED detection and segmentation recognition based on deep learning for optical camera communication. Optoelectronics Letters, 2022, 18(8): 508‒512 https://doi.org/10.1007/s11801-022-2026-5

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