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Real-time Automatic License Plate Recognition System using YOLOv4

Ju-Yeong Sung, Saet-Byeol Yu, Se-ho Park Korea

202045 citationsDOI

Abstract

We introduce a real-time Automatic License Plate Recognition system that is computationally lighter by eliminating the ROI setting step, without deteriorating recognition performance. Conventional license plate recognition systems exhibit two main problems. First, clear license plate visibility is required. Second, processing actual field data is computationally intensive and the ROI needs to be set. To overcome these problems, we performed plate localization directly on the entire image, and conducted research taking low quality license plate detection into account.We aim to recognize the license plates of cars moving at high speeds on the road as well as stationary cars using the NVIDIA Jetson TX2 module, which is an embedded computing device.

Topics & Concepts

LicenseComputer scienceComputer visionArtificial intelligenceVisibilityField (mathematics)Set (abstract data type)Image processingRegion of interestIntelligent transportation systemPattern recognition (psychology)Image (mathematics)EngineeringOperating systemPure mathematicsOpticsPhysicsCivil engineeringMathematicsProgramming languageVehicle License Plate RecognitionAdvanced Neural Network ApplicationsSmart Parking Systems Research
Real-time Automatic License Plate Recognition System using YOLOv4 | Litcius