Research on License Plate Location in Different Scenes

Abstract

There are many license plate location methods, but the factors affecting the extraction of license plate information are different in different scenarios. Current research has not systematically classified the scenarios applicable to the license plate location method according to the actual situation. In order to locate the license plate accurately and quickly in different environments. This paper makes experiments, comparisons and analyses on the location effects of different license plate location algorithms in different situations, and obtains the applicable scenarios of each license plate location algorithm: the color segmentation algorithm is suitable for the case of high brightness, the Canny operator edge detection method for license plate location is suitable for the case of noise, and the combination of blind deconvolution, morphology and texture feature analysis. License Plate Recognition and Location Algorithms are suitable for the situation of motion blur, noise and other interference factors.