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License plate generation method based on generative adversarial network

A license plate and network technology, applied in the computer field, can solve the problem of random license plate image labels, and achieve the effect of enriching license plate image data sets, high application value, and covering a wide range of scenes.

Pending Publication Date: 2022-04-01
FUZHOU UNIV
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Problems solved by technology

[0004] In view of this, the purpose of the present invention is to provide a license plate generation method based on generative confrontation network, based on the encoding-decoding network structure, so that the license plate image with labels can be generated according to the template license plate, which solves the problem of traditionally generated license plate images. Questions tagged random

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  • License plate generation method based on generative adversarial network
  • License plate generation method based on generative adversarial network
  • License plate generation method based on generative adversarial network

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Embodiment Construction

[0057] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0058] Please refer to figure 1 , the present invention provides a method for generating a license plate based on generating an adversarial network, comprising the following steps:

[0059] Step S1: obtain the license plate character base and the background image for generating the template license plate;

[0060] Step S2: Randomly select characters according to the license plate composition, use OpenCV to insert the characters into the background image, synthesize the template license plate, and carry out image enhancement to the template license plate to obtain the template license plate image set;

[0061] Step S3: build the license plate generation network based on the encoding-decoding structure, including the license plate encoding network based on the convolutional neural network, the decoding generation network based on StyleGAN2, the license p...

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Abstract

The invention relates to a license plate generation method based on a generative adversarial network. The method comprises the following steps: S1, obtaining a license plate character library and a background image used for generating a template license plate; s2, randomly selecting characters according to license plate composition, placing the characters into the background image by using OpenCV, synthesizing a template license plate, and performing image enhancement on the template license plate; s3, constructing a license plate generation network based on a coding-decoding structure; s4, constructing a training set based on the license plate image in the real scene and the template license plate image set; and S5, based on the training set, training a license plate generation network based on a coding-decoding structure by using an adversarial generation model to obtain a trained license plate generation network for generating a license plate image with a label. Based on an encoding-decoding network structure, the license plate image with the label can be generated according to the template license plate, and the problem that the label of the traditionally generated license plate image is random is solved.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a license plate generation method based on a generative confrontation network. Background technique [0002] In the automatic license plate recognition system, license plate recognition is a very critical part, and its performance affects the final recognition result. In the current license plate recognition method based on deep learning, the license plate dataset has a significant impact on the training of the recognition network. Through large-scale, wide-coverage training set training, the recognition network can have better generalization and stronger robustness. However, limited to the collection of license plate data sets, it faces various challenges such as collection difficulties, high labeling costs, and data privacy. It is difficult to obtain a large number of license plate datasets covering a wide range of scenarios. Therefore, it is urgently required to use image...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V20/62G06V30/148G06V30/146G06V30/19G06V10/25G06V10/774G06V10/82G06K9/62G06N3/04G06N3/08
Inventor 柯逍曾淦雄黄旭
Owner FUZHOU UNIV
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