License plate recognition method based on deep convolutional neural network

A neural network and license plate recognition technology, applied in the field of license plate recognition based on deep convolutional neural network, can solve the problems of confusing special character recognition and low recognition rate.

Inactive Publication Date: 2017-02-22
ANHUI SUN CREATE ELECTRONICS
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Problems solved by technology

[0003] The license plate recognition method in the prior art still has a low recognition rate for the license plate in bad weather, at night, and when the angle is too inclined. The character blur affects the feature extraction, and special character recognition is easily

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  • License plate recognition method based on deep convolutional neural network
  • License plate recognition method based on deep convolutional neural network
  • License plate recognition method based on deep convolutional neural network

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[0073] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0074] Such as figure 1 , 2 As shown, a license plate recognition method based on deep convolutional neural network, including the following steps:

[0075] S1. Carry out license plate detection on the vehicle image to obtain the license plate;

[0076] S2. Carry out image segmentation on the detected license plate to obtain license plate characters, and use the license plate characters as training samples;

[0077] S3. Randomly sampling the training sample...

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Abstract

The invention belongs to the technical field of image processing and mode recognition and particularly relates to a license plate recognition method based on a deep convolutional neural network. The method includes: performing license plate detection on vehicle images, performing image segmentation on detected license plates to obtain license plate characters, using the license plate characters as training samples to obtain a training sample block set, inputting the training sample block set into a deep auto-encoder to train the deep auto-encoder, using the trained deep auto-encoder as the convolution kernel of the convolutional neural network, extracting the convolution features of the training sample block set, performing pooling operation on the convolution features of the training sample block set to obtain feature vectors, performing normalization processing on the feature vectors, loading the feature vectors after the normalization processing into an SVM classifier to train the SVM classifier, and testing to-be-recognized vehicles. By the method, license plate recognition accuracy can be increased, and license plate character recognition rate and robustness can be increased when the license plate characters are located in severe environments.

Description

technical field [0001] The invention belongs to the technical field of image processing and pattern recognition, in particular to a license plate recognition method based on a deep convolutional neural network. Background technique [0002] License plate recognition technology is a key technology in modern intelligent transportation systems and has been widely used in daily life. Today, deep learning has become a hot spot in the field of computer pattern recognition. Using deep learning algorithms can improve the recognition rate of license plate recognition. It is of great significance to improve the robustness of the license plate recognition system. [0003] The license plate recognition method in the prior art still has a low recognition rate for the license plate in bad weather, at night, and when the angle is too inclined. The character blur affects the feature extraction, and special character recognition is easily confused, such as 8 and B, 2 and Z, 0 and D, 5 and S...

Claims

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Application Information

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IPC IPC(8): G06K9/32G06K9/62
CPCG06V20/63G06V20/625G06F18/2148G06F18/2411
Inventor 王卫陈昌健卫彪李三菊何丹娜李志学唐飞刘江明尚兵兵刘成龙
Owner ANHUI SUN CREATE ELECTRONICS
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