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Car license plate recognition system is based on car license plate for a specific target dedicated computer intelligent system, image processing and computer vision applications in the field of intelligent transportation is one of the important research directions in traffic detection, airport, port, community management of vehicles , non-stop automatic toll collection, running red lights and other illegal vehicles and vehicle security alarm monitoring and other fields has been widely used, and has broad application prospects. Under normal circumstances, automatic license plate recognition system software to complete some of the major functions: image preprocessing, license plate positioning plates tilt correction, character segmentation, character recognition. Taking into account the experimental conditions and time constraints, this paper is designed around the following sections: vehicle positioning, tilt correction, character segmentation, character recognition. This article presents only a part of these four effective solution strategies to complete the experiment. ① image preprocessing sections: a brief introduction to some of the images used in this article pretreatment technology, including: gray-scale image, image enhancement, mathematical morphology, image binarization, edge detection, and gives the respective the results. ② plate location: Based on the extensive analysis and comparison of existing methods based on mathematical morphology is proposed based on the projection of the license plate location algorithm, the method using Top-Hat transform, gray image by gray mathematical morphology pre-processing of the image, and then use the connectivity analysis method to get the license plate posture candidate region, and finally combining the license plate area projection features locate the license plates. Effectively solve the problem of natural background plates positioning, while the method is suitable for multi-plate positioning applications. Experiments show that: the algorithm has a positioning accuracy rate (up to 97.4%), robustness, speed, etc.. ③ tilt correction and character segmentation: the license plate on the basis of accurate positioning, the application of the minimum variance based on edge points and the Radon transform projection method of license plate has been corrected, the dichotomy proposed based on projection and prior knowledge of character segmentation algorithm, experimental results show that the method is fast segmentation, segmentation accuracy of character adhesion, fracture, tilt-insensitive. ④ character recognition: Taking into account the limited sample images collected experimental and traditional character recognition method, this paper proposes a combination of characteristics and based on support vector machine license plate character recognition method, the algorithm first one-dimensional wavelet multi-angle projection and Pseudo-Znerike not variable torque plate character image feature extraction, and then use bilinear search method, using the extracted features training mission support vector machine learning classifier highest precision, and then use this classification for classification and identification plate character, with plenty of samples of the system testing, license plate recognition rate of 97.6% overall, through comparative studies to verify the effectiveness of the method and advanced. Based on theoretical research, and presents the corresponding algorithm using Matlab programming implementation.
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