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License Plate Recognition System based on Improved BP Neural Network

by Tingyu Ma, Tao Wang, Jinchao Shi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 176 - Number 21
Year of Publication: 2020
Authors: Tingyu Ma, Tao Wang, Jinchao Shi
10.5120/ijca2020920204

Tingyu Ma, Tao Wang, Jinchao Shi . License Plate Recognition System based on Improved BP Neural Network. International Journal of Computer Applications. 176, 21 ( May 2020), 27-34. DOI=10.5120/ijca2020920204

@article{ 10.5120/ijca2020920204,
author = { Tingyu Ma, Tao Wang, Jinchao Shi },
title = { License Plate Recognition System based on Improved BP Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { May 2020 },
volume = { 176 },
number = { 21 },
month = { May },
year = { 2020 },
issn = { 0975-8887 },
pages = { 27-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume176/number21/31326-2020920204/ },
doi = { 10.5120/ijca2020920204 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:41:14.257680+05:30
%A Tingyu Ma
%A Tao Wang
%A Jinchao Shi
%T License Plate Recognition System based on Improved BP Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 176
%N 21
%P 27-34
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

With the increase in the number of vehicles, the license plate recognition system has gradually become a hot spot in scientific research. In this paper, we address the shortcomings of BP neural networks and combine it with the image processing technology of license plate characters, propose a license plate recognition system based on improved BP neural network for license plate recognition. The system mainly includes four modules: license plate image preprocessing, license plate positioning, character segmentation and classification recognition. Firstly, image preprocessing is implemented through image graying, gray stretching, and image binarization. Secondly, edge detection and morphological processing are used to determine the license plate area. Thirdly, the character string of the license plate is segmented. Finally, two corresponding BP neural networks are designed to classify and recognize the license plate characters based on the characteristics of the license plates in China to obtain the recognition results.

References
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Index Terms

Computer Science
Information Sciences

Keywords

LPR License plate localization Character segmentation Classification recognition

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