Application of License Plate Recognition Based on Improved Neural Network

License plate recognition is core technology in the modern intelligent transportation management.The BP neural network has slow convergence speed,and is easy to fall into the local optimal problem.A license plate recognition algorithm is proposed based on improved BP neural network.Firstly the vehicle license plate characters are normalized,some useless information is eliminates,and character features are extracted.Then the BP neural network is improved by momentum factor and adaptive learning speed,and its convergence rate jis accelerated.Finally the extracted character features are input into the BP neural network for training and recognition.Simulation experiments show that compared with other license plate recognition algorithm,the improved BP neural network improves license plate recognition accuracy and recognition efficiency,and it is very suitable for real-time modern intelligent traffic management.