License Plate Character Recognition Based on BP Neural Network

Character recognition plays an important role in the automatic license plate recognition(ALPR) system.The license plate recognition was done in the several steps.First,the license plate was preprocessed by image processing algorithms.Then,each character was separated by the vertical projection algorithms.In the last step,all of characters set of license plate were recognized and the features were extracted from each character to lump into a vector as input of the BP neural network.The system worked under variable illumination,variable size of plate and dynamic backgrounds,especially similar characters.The correct recognition rate was very high.Besides,BP neural network train sample attained from the character itself was compared and analyzed.The experimental results demonstrated the great robustness and efficiency of the method.