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License Plate Recognition Algorithm for Passenger Cars in Chinese Residential Areas

This paper presents a solution for the license plate recognition problem in residential community administrations in China. License plate images are pre-processed through gradation, middle value filters and edge detection. In the license plate localization module the number of edge points, the lengt...

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Detalles Bibliográficos
Autores principales: Jin, Lisheng, Xian, Huacai, Bie, Jing, Sun, Yuqin, Hou, Haijing, Niu, Qingning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3436033/
https://www.ncbi.nlm.nih.gov/pubmed/22969404
http://dx.doi.org/10.3390/s120608355
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author Jin, Lisheng
Xian, Huacai
Bie, Jing
Sun, Yuqin
Hou, Haijing
Niu, Qingning
author_facet Jin, Lisheng
Xian, Huacai
Bie, Jing
Sun, Yuqin
Hou, Haijing
Niu, Qingning
author_sort Jin, Lisheng
collection PubMed
description This paper presents a solution for the license plate recognition problem in residential community administrations in China. License plate images are pre-processed through gradation, middle value filters and edge detection. In the license plate localization module the number of edge points, the length of license plate area and the number of each line of edge points are used for localization. In the recognition module, the paper applies a statistical character method combined with a structure character method to obtain the characters. In addition, more models and template library for the characters which have less difference between each other are built. A character classifier is designed and a fuzzy recognition method is proposed based on the fuzzy decision-making method. Experiments show that the recognition accuracy rate is up to 92%.
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spelling pubmed-34360332012-09-11 License Plate Recognition Algorithm for Passenger Cars in Chinese Residential Areas Jin, Lisheng Xian, Huacai Bie, Jing Sun, Yuqin Hou, Haijing Niu, Qingning Sensors (Basel) Article This paper presents a solution for the license plate recognition problem in residential community administrations in China. License plate images are pre-processed through gradation, middle value filters and edge detection. In the license plate localization module the number of edge points, the length of license plate area and the number of each line of edge points are used for localization. In the recognition module, the paper applies a statistical character method combined with a structure character method to obtain the characters. In addition, more models and template library for the characters which have less difference between each other are built. A character classifier is designed and a fuzzy recognition method is proposed based on the fuzzy decision-making method. Experiments show that the recognition accuracy rate is up to 92%. Molecular Diversity Preservation International (MDPI) 2012-06-15 /pmc/articles/PMC3436033/ /pubmed/22969404 http://dx.doi.org/10.3390/s120608355 Text en © 2012 by the authors; licensee MDPI, Basel, Switzerland This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Jin, Lisheng
Xian, Huacai
Bie, Jing
Sun, Yuqin
Hou, Haijing
Niu, Qingning
License Plate Recognition Algorithm for Passenger Cars in Chinese Residential Areas
title License Plate Recognition Algorithm for Passenger Cars in Chinese Residential Areas
title_full License Plate Recognition Algorithm for Passenger Cars in Chinese Residential Areas
title_fullStr License Plate Recognition Algorithm for Passenger Cars in Chinese Residential Areas
title_full_unstemmed License Plate Recognition Algorithm for Passenger Cars in Chinese Residential Areas
title_short License Plate Recognition Algorithm for Passenger Cars in Chinese Residential Areas
title_sort license plate recognition algorithm for passenger cars in chinese residential areas
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3436033/
https://www.ncbi.nlm.nih.gov/pubmed/22969404
http://dx.doi.org/10.3390/s120608355
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