The Study Of The License Plate Recognition Based On The Image Processing

License plate recognition technology has been more and more important with great application fields in our life. Location, character segmentation and character recognition of vehicle license are three key steps of license plate recognition. License plate recognition technology is studied in the thesis from the three steps.In the license plate location stage, the author has utilized an location search algorithm based on the line. This method turned out to be accurate, fast and coincident with the actual fact. In the character isolation stage, firstly, use Hough transfer to do the tilt correction to the vehicle license plate; then, delete the edge of the character image; lastly, a segmentation method of vertical projection combined with templates matching is brought forward and it solves those problems such as non-integrity, position shift, character abrasion, character distortion, and so on. In the character recognition stage, Support Vector Machine (SVM) is used to recognize the characters of vehicle license plates in the thesis. According to the arrayed feature of the plates, four types of classifying systems including Chinese characters classifying system, letter classifying system, figure and letter classifying system, figure classifying system, are configured. Every character in a vehicle license plate will be recognized by the corresponding classifying system according to its sequence number in the plate. The characters of the license are recognized by combination of the order results. The experimental result shows high recognition rate and fast speed for all characters of a vehicle license plate. The paper also has carried on the discussion for strengthens to the contrast, the correction for grade binaryzation of the very important imagery processing.Based on the experiments dealing with images taken under various real world conditions, the results prove that this proposed method can relatively locate license plate and segment characters. It shows that the performance of the system is promising, robust and timely.