Real-time Video-based License Plate Recognition System

Based on computer image processing and recognition technology, vehicle recognition system achieves the automatic recognition of license plate reading, vehicle identification greatly improved work efficiency, without increasing the impact on traffic flow. License Plate Recognition System in traffic control, traffic management, traffic accidents and many other aspects of automatic forecasting have played an important role, is widely used in car parks, ports and airports, urban monitoring systems, road traffic observation stations, bridges and roads closed fee station, highway traffic observation station certification number plate, the actual traffic system, the paper license plate recognition system for the current main problems in the design to achieve real-time video-based license plate recognition system and related algorithms optimized.For the difficulties of positioning vehicle plate, this dissertation solves the problem by the location algorithm based on a fixed color matching. As the background color and character color of the plate is determined by several characteristics with the composition of extracted color image. Then, the plate's region is located by the texture of vehicle plate. This algorithm has a higher accuracy and shorter periods of time, it can still reach 96% of the targeted rate by the characteristics of the complex or exceptional circumstances. This dissertation presents a stochastic line detection method to locate the license plate of the border, and the algorithm can resolve the tilt angle of the license plate. In comparison with Hough method, this algorithm has less calculation and takes shorter periods of time. In this dissertation after analyzing the advantages and disadvantages of global and local algorithms, a new algorithm is put forward which is derived from the combination of them. The new algorithm can keep the details of the image, and effectively remove artifacts possess interference. After image binarization, the characters on the plate split into separate characters, and the characters are recognized by BP neural network, average rate of recognition is 95.7%. By using the above optimization algorithm, a real-time video-based vehicle plate recognition system is achieved in-depth analysis of demand on the vehicle plate recognition system.