A license plate detection method based on depth learning

A deep learning and license plate technology, applied in the field of license plate recognition based on deep learning, can solve the problems of low accuracy and poor real-time performance, and achieve the effect of ensuring accuracy, real-time performance and accuracy

Active Publication Date: 2019-01-25
TRAFFIC MANAGEMENT RES INST OF THE MIN OF PUBLIC SECURITY
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  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In order to solve the problems of poor real-time performance and low accuracy in the real environment of existing license plate recognition methods, the present invention provides a license plate

Method used

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  • A license plate detection method based on depth learning
  • A license plate detection method based on depth learning
  • A license plate detection method based on depth learning

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Embodiment Construction

[0049] Such as Figure 1~Figure 2As shown, the present invention is a license plate recognition method based on deep learning, and the inherent color attribute of the license plate is added to YOLO (J. Redmon, S. Divvala, R. Girshick, A. Farhadi. You Only LookOnce: Unified, Real-Time Object Detection. CVPR, 2016) model to construct a license plate detection model with strong generalization ability, high detection and positioning accuracy, detect the passing pictures taken by the input bayonet monitoring equipment, and obtain the area position of the license plate; then Slanted license plate regions were corrected using the Radon (SR Deans, the Radon transform and some of its application. John Wiley & Sons Inc New York, 1983) transform, using both color and edges (E. R. Lee, P. K. Kim, and H. J. Kim, Automatic recognition of a car license plate using color image processing.ICIP, 1994) and other clues to fine-tune the license plate area, and finally send the fine-tuned license p...

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Abstract

The invention provides a license plate recognition method based on depth learning, which can self-adaptively obtain license plate characteristic information under different scenes, and simultaneouslyimproves the accuracy rate of license plate recognition. The invention adds the inherent color attribute of the license plate into the YOLO model to construct a license plate detection model with strong generalization ability and high detection and positioning accuracy, detects the passing picture taken by the input bayonet monitoring device, and obtains the area position of the license plate. Then, the inclined license plate area is corrected by Radon transform, and the license plate area is fine-tuned by color and edge. Finally, the fine-tuned license plate area is sent to CRNN network whichis constrained by license plate coding rules to recognize the license plate number.

Description

technical field [0001] The invention relates to the technical field of image recognition in intelligent traffic control, in particular to a deep learning-based license plate recognition method. Background technique [0002] Motor vehicle license plates are used as the unique identification symbols for motor vehicle management by national traffic management departments. The detection and identification of license plate numbers play an extremely important role in intelligent transportation systems; the existing license plate recognition methods are usually divided into three steps: the first The first step is to use the characteristics of the license plate to quickly locate the position of the license plate through clues such as color, edge, and texture, and obtain the candidate area of ​​the license plate target; the second step is to use SIFT ((Scale-invariant feature transform, scale-invariant feature transformation) , LBP (Local Binary Patterns, local binary pattern) and o...

Claims

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Application Information

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IPC IPC(8): G06K9/34G06K9/32G06N3/04
CPCG06V10/243G06V10/267G06V20/625G06N3/045
Inventor 蔡岗刘敏张森孙正良黄淑兵李小武吴晓峰缪新顿孔晨晨李杰
Owner TRAFFIC MANAGEMENT RES INST OF THE MIN OF PUBLIC SECURITY
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