Study On Vehicle License Plate Recognition Algorithm Based On Structure Of Vehicle's Numerals And Letters

Automatic recognition of vehicle license plate is one of the significant research subjects for applying computer vision, image processing and pattern recognition to the intelligent transportation and an important link in putting intelligent traffic management into practice. A typical automatic recognition system of vehicle license plate is composed of image capture, license plate location, character segmentation and character recognition etc.Algorithms of the main part of the system, including license plate location,character segmentation and character recognition, are respectively provided and realized.This paper researches on the algorithms of vehicle license plate location. Edge detection , image morphology and clustering analysis are used to locate the backup area of the plate in which the fuzzy decision is used to position the real area. This algorithm is excellent in accuracy and completely applicable to the complex traffic scenes.In the algorithm of the character segmentation, homomorphic filtering is used to eliminate the influence from nonlinear illuminations, Hough transform is used to update the inclination of the plate and vertical projection and deformable template are used to segment characters. It has an advantage of high percentage of segmentation.The structure features are used to recognize characters in the character recognition. For every character segmented from a vehicle plate,if the pixel gray is larger than the threshold value which is decided artifical,labeling factually,and if the pixel gray is smaller than the threshold value,labeling "0" instead with different color.Apply longitudinal structure tree classifying and structure units combination to recognize respectively and summarize the two methods.The two methods obtains excellent results in the practice. It is proved to be a higher accuracy, faster and elegant way of recognition, and satisfy the requirements of practical application.