License plate character identification method based on refined character classifier

Abstract

The invention provides a license plate character identification method based on a refined character classifier. The license plate character identification method comprises the steps of performing preprocessing on a to-be-trained license plate character image and obtaining a plurality of training samples; coarsely classifying the training samples into 34 classes according to the character meaning; refining each same-class training sample which is obtained through coarse dividing to a plurality of subclasses; training the refined training samples by means of an SVM classifier, and obtaining the refined character classifier; performing preprocessing on a to-be-detected license plate character image and obtaining a testing sample; and identifying the testing sample by means of the refined character classifier, and obtaining the characters in the to-be-detected license plate character image. According to the license plate character identification method, through performing refined classification on the characters of the license plate, not only is training complexity of the classifier reduced, but also the refined character classifier is used for identifying the characters of the license plate, thereby preventing a problem of obscure same-class characteristic caused by character fuzzy or character inclination or different font, and improving a recognition rate of the characters of the license plate.

Description

technical field [0001] The invention relates to the technical field of license plate character recognition, in particular to a license plate character recognition method based on a refined character classifier. Background technique [0002] With the rapid development of intelligent transportation in recent years, automatic license plate recognition systems have been widely used. Character recognition in the license plate recognition process is a very critical step, and commonly used character recognition methods include template matching or training classifiers through large amounts of data. When training the classifier, due to the characters being blurred or skewed during processing, or the fonts are different, the characters that originally belonged to one category have not very similar features, which increases the difficulty of the classifier during the training process. Reduced character recognition rate. Contents of the invention [0003] The object of the pres...

AI Technical Summary

Problems solved by technology

When training the classifier, due to the characters being blurred or skewed during processing, or the fonts are different, the characters that originally belonged to one category have not very similar features, which increases the difficulty of the classifier during the training process. Reduced character recognition rate

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