License plate type identification method and device

Abstract

The invention provides a license plate type identification method and device, and the method comprises the steps: carrying out the positioning segmentation of a license plate in a license plate imagethrough a pre-built license plate region detection model; correcting the segmented license plate; according to the corrected license plate, obtaining a license plate type to which the license plate belongs through a pre-established license plate type identification model; wherein the license plate type comprises a preset first type license plate and a preset second type license plate; when the license plate belongs to the first type license plate, taking the license plate type output by the license plate type identification model as a license plate type identification result of the license plate image; when the license plate belongs to a second type of license plate, performing character segmentation on the license plate, and obtaining a character located at a preset position in the license plate as a to-be-identified character; obtaining a character recognition result through a preset character recognition model according to the to-be-recognized character; obtaining a license plate type recognition result of the license plate image according to the character recognition result. According to the method, the accuracy of identifying various license plate types can be improved.

Description

technical field [0001] The invention belongs to the technical field of image recognition, and more specifically relates to a license plate type recognition method and equipment. Background technique [0002] With the development of artificial intelligence and computer vision technology, license plate type recognition technology has been widely used in many traffic management and law enforcement systems. In the prior art, the license plate type recognition generally uses a convolutional neural network for recognition, but this recognition method has stricter data requirements and requires a large amount of data for network training, but some special license plate data cannot meet the training recognition standards, for example, In the training sample collection stage, since vehicle data from Hong Kong, Macao and Taiwan, license plate data of police cars, armed police, and military vehicles are rarely encountered, a large number of license plate data collected are common licen...

AI Technical Summary

Problems solved by technology

In the prior art, the license plate type recognition generally uses a convolutional neural network for recognition, but this recognition method has stricter data requirements and requires a large amount of data for network training, but some special license plate data cannot meet the training recognition standards, for example, In the training sample collection stage, since vehicle data from Hong Kong, Macao and Taiwan, license plate data of police cars, armed police, and military vehicles are rarely encountered, a large number of license plate data collected are common license plate data such as single-layer blue and yellow plates, resulting in insufficient training samples. The distribution is unbalanced, which affects the training effect of the neural network, so that the accuracy of license plate type recognition in actual application scenarios

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