European Union Dataset and Annotation Tool for Real Time Automatic License Plate Detection and Blurring

Abstract

Automatic license plate detection has always been a popular topic in intelligent transport systems. In recent years, many approached the problem using artificial intelligence and machine learning techniques. Sufficient amount of good quality data is critical for machine learning, however, most of the existing open source license plate datasets are either restrictive in nature or do not have enough number of images to allow training a robust license plate detection network. In this paper, the THI License Plate Dataset (TLPD) is presented. It has more than 17,000 vehicle images and 18,000 labelled license plates in it. It is one of the largest publicly available European Union license plate datasets. The images in the dataset capture license plates at different angles and distances in relation to the camera. They are also taken under different illumination and weather conditions, making the dataset suitable for training robust license plate detectors that could work in various scenarios. A fast labelling tool for single class labelling is also presented in this paper. This tool was used to label the license plates in TLPD. This paper also introduces two license plate detection networks trained with data from TLPD. The networks work robustly under various scenarios, achieving precision and recall value of 93% under day and night conditions and 87% under heavy snowing condition.