License plate recognition method and system

Abstract

The invention discloses a license plate recognition method and system, and the method comprises the following steps: collecting a vehicle image; carrying out the filtering of the vehicle image, and carrying out the edge detection of the vehicle image through a Canny operator, so as to convert the vehicle image into an edge binary image; scanning the edge binary image, so as to obtain license plate candidate regions according to the edge spacing and edge jump; locating the license plate in the license plate candidate regions according to the vertical edge features and morphological expansion of the license plate; searching a plurality of characters from the license plate according to the contour features of a single character, and removing the pseudo characters in the characters according to a license plate template; carrying out the recognition of the characters through an SVM classifier, and determining the license plate number of a vehicle according to a recognition result. The method can carry out the precise positioning and character segmentation of the license plate, and improves the character recognition rate of the license plate.

Description

technical field [0001] The present invention relates to the technical field of vehicles, in particular to a method and system for identifying a license plate. Background technique [0002] At present, regarding vehicle license plate recognition, there is a license plate character recognition method based on multi-feature fusion. The steps are: detecting the vehicle in the video and locating and segmenting the license plate in the vehicle; performing projection analysis on the segmented license plate , segment and extract 7 valid characters in the license plate; perform morphological processing on the segmented character images, and extract three features of the license plate characters for effective fusion; use the support vector machine to train the fusion features to generate a license plate character classifier , to effectively recognize vehicle license plate characters in real-time video. [0003] However, the character segmentation algorithm in the above method is main...

AI Technical Summary

Problems solved by technology

However, because the captured image is affected by various environmental factors, there will be large noise interference in the license plate image, and some information will be lost during the image binarization process, which often causes character adhesion and character breakage, and the vertical projection method usually It can only segment the license plate characters in an ideal environment, but cannot accurately segment the characters sticking and character breaks, and has poor adaptability to complex environments, which leads to high empirical components of the license plate character features extracted by this method, and the license plate recognition effect is not good.

Images