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Robust Chinese license plate detection and correction method in non-controllable environment

A license plate detection and license plate technology, applied in the field of image processing, can solve problems such as inaccurate positioning and slow speed, and achieve strong generalization and good robustness

Pending Publication Date: 2022-05-10
BEIJING UNIV OF TECH
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Aiming at the problems of inaccurate positioning and slow speed in license plate detection in an uncontrollable environment, the present invention proposes a robust Chinese license plate detection method in an uncontrollable environment

Method used

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  • Robust Chinese license plate detection and correction method in non-controllable environment
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  • Robust Chinese license plate detection and correction method in non-controllable environment

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Embodiment Construction

[0028] The specific implementation manners of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0029] The overall block diagram of the Chinese license plate detection method proposed by the present invention is composed of four parts: input preprocessing, depth feature extraction, license plate coordinate position regression, and license plate correction. For details, see figure 1 .

[0030] The implementation details of each step are as follows:

[0031] Step 1: Create a license plate detection dataset

[0032] The present invention obtains 100,000 license plate images by downloading from the Internet, collecting on-site, and using existing data sets, etc., and manually marks the license plate area in it, and constructs a license plate detection data set for training a deep convolutional neural network model .

[0033] Step 2: Input license plate preprocessing

[0034] Step 2.1: Input image size normalization process...

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Abstract

The invention discloses a robust Chinese license plate detection and correction method in a non-controllable environment, and belongs to the field of image processing. Most of current license plate detection methods adopt matrix frame positioning, and in a non-controllable environment, if a license plate is seriously inclined or deformed, the license plate positioning is inaccurate, that is, more backgrounds exist in a positioned license plate area or the positioning is incomplete, the subsequent license plate recognition is interfered, and the recognition accuracy is influenced. According to the Chinese license plate detection method provided by the invention, by introducing ACON, RBN and deformable convolution, the feature extraction capability of the model can be improved, a detection head is improved, a corresponding coordinate regression formula is designed, any inclined license plate can be accurately positioned, and an ideal detection result can be obtained in various complex non-controllable environments.

Description

technical field [0001] The invention belongs to the field of image processing, and specifically relates to technologies such as Chinese license plate detection and deep learning. Background technique [0002] The license plate number reflects the information of the vehicle and its owner. Accurate identification of the license plate number is a key step in intelligent transportation, and the accuracy of license plate detection greatly affects the accuracy of license plate recognition. At present, license plate detection and recognition have been widely used in some controllable environments, such as parking lots, high-speed toll intersections, and so on. Most of the current license plate detection methods use matrix frame positioning. In an uncontrollable environment, if the license plate is severely tilted or deformed, the license plate positioning will be inaccurate, that is, there is more background in the license plate area or the positioning is incomplete. , will interf...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V20/00G06N3/04G06N3/08G06V10/44G06V20/62
CPCG06N3/08G06N3/045
Inventor 卓力安鑫李嘉锋
Owner BEIJING UNIV OF TECH
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