Real-time license plate detection for non-helmeted motorcyclist using YOLO

作者：Yonten Jamtsho, Panomkhawn Riyamongkol, Rattapoom Waranusast · 发表于：ICT Express · 年份：2020 · DOI：10.1016/j.icte.2020.07.008 · 被引用次数：97 · 研究领域：Vehicle License Plate Recognition、Advanced Neural Network Applications、IoT and GPS-based Vehicle Safety Systems

Nowadays, detection of license plate (LP) for non-helmeted motorcyclist has become mandatory to ensure the safety of the motorcyclists. This paper presents the real-time detection of LP for non-helmeted motorcyclist using the real-time object detector YOLO (You Only Look Once). In this proposed approach, a single convolutional neural network was deployed to automatically detect the LP of a non-helmeted motorcyclist from the video stream. The centroid tracking method with a horizontal reference line was used to eliminate the false positive generated by the helmeted motorcyclist as they leave the video frames. The overall LP detection rate was 98.52%.