Real-time license plate detection for non-helmeted motorcyclist using YOLO
Yonten Jamtsho, Panomkhawn Riyamongkol, Rattapoom Waranusast
Abstract
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%.
Topics & Concepts
LicenseConvolutional neural networkComputer scienceArtificial intelligenceObject detectionCentroidComputer visionPattern recognition (psychology)Operating systemVehicle License Plate RecognitionAdvanced Neural Network ApplicationsIoT and GPS-based Vehicle Safety Systems