License plate recognition method based on sequence learning

Abstract

The invention discloses a license plate recognition method based on sequence learning, and belongs to the technical field of intelligent traffic. A license plate image is changed into a sequence composed of candidate characters through a deep neural network used for character detection and recognition, then the sequence is input into a sequence conversion model obtained through training, a new character index sequence is obtained, and finally original candidate characters are recombined according to indexes to obtain a license plate recognition result. According to the license plate recognition method based on sequence learning obtained through the technology, a machine autonomously learns license plate character selection, rejection and permutation combination rules, the pressure of manually designing heuristic rules is reduced, learning experience is achieved with the help of a large number of data samples, and a sequence model can be more flexible in the aspect of the recognition problem of multi-standard license plates. Compared with a traditional sequence processing method, such as hidden Markov, the method has the advantages that the connection of the sequence elements can be found in long-time dependence, and a better sequence conversion result is obtained.

Description

technical field [0001] The invention relates to the technical field of intelligent transportation, and specifically designs a license plate recognition method based on sequence learning. Background technique [0002] Automatic license plate recognition is a technology that combines multiple tasks such as image processing, machine learning and pattern recognition. After decades of development, license plate recognition technology has entered the stage of large-scale commercial use, and its application fields include access control in public places, traffic checkpoint monitoring, and traffic intersection monitoring. [0003] With the development of intelligent transportation technology, the commercial license plate recognition system has applied deep learning to the solution of practical problems, and announced that its license plate recognition rate is as high as 99%. Literature (Y.Zhao, Z.Yu, and X.Li, "Evaluationmethodology for license plate recognition systems and experim...

AI Technical Summary

Problems solved by technology

[0006] To sum up, the current license plate recognition methods are facing the following problems: 1) A variety of license plate formats is one of the main challenges for related research; 2) There are missing and multiple detections in the license plate recognition method based on character detection; 3) Although the artificial heuristic method is efficient and accurate, the design of the heuristic rules is complicated, and different strategies need to be adopted for different license plates

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