Robust license plate and logo recognition method

Abstract

The invention discloses a robust license plate and logo recognition method. The method based on Adaboost detection, SVM screening and texture analysis edge removal is adopted to perform license plate precise detection to effectively respond to different scenes, illuminations, viewing angles, resolutions and the like, and a detected license plate region only contains less background. License plate recognition is performed mainly by using maximum stable extremal region detection assisted by sliding window detection in cooperation with energy optimization, thus, characters which are difficult to process under the conditions of license plate contamination, insufficient definitions and the like based on a character segmentation method traditionally can be effectively detected, character detection and recognition are performed synchronously, and the traditional mode of ''recognition after segmentation'' is broken. A feature code weighted based on confidence is adopted to express a logo sample, a group-based sparse discriminative dictionary pair model is utilized to recognize logo features of the code, and the method has high robustness on the logo sample containing a complex background.

Description

technical field [0001] The invention relates to the field of intelligent transportation, in particular to a robust method for identifying license plates and vehicle logos. Background technique [0002] In recent years, with the gradual improvement of people's quality of life, the demand for cars is also increasing. In order to improve the efficiency of road traffic management and effectively deal with traffic problems such as car theft and illegal driving, intelligent transportation systems have emerged, and its key technologies include license plate and vehicle logo recognition. The license plate is the unique identification of the vehicle, and automatic and correct recognition of the license plate is conducive to improving the efficiency of traffic and vehicle management. However, only relying on license plate recognition technology is not enough to solve the increasingly complex traffic problems. As the most prominent mark to distinguish different car manufacturers, the...

AI Technical Summary

Problems solved by technology

Although the above methods have achieved good results, most of them are based on ideally positioned and segmented car logo samples, and the accuracy of the current existing methods in car logo positioning is often not satisfactory, so these rely on The method of accurate positioning and segmentation is difficult to effectively deal with car logo pictures with complex backgrounds in practical applications

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