Vehicle License Plate Recognition Algorithm Based on Deep Learning

Abstract

With the gradual increase of car ownership in China, license plate recognition plays an important role in intelligent vehicle control system. The existing vehicle number recognition algorithms have slow recognition speed and low accuracy, and are easy to be affected by the light, the position angle of the license plate and the relative fixed position of the camera. The Faster-RCNN based on pattern analysis method locates the license plate, generates the license plate extraction frame and extracts the license plate; Use VGGnet network model to recognize characters, and finally complete the recognition of car license plate. Training and testing are carried out in a great quantity of data sets. The simulation results show that the network model combining fast RCNN and VGGnet can recognize the license plate with an accuracy of 99.2% in a complex environment, and the recognition accuracy is better than other algorithms.