Automated license plate recognition of Philippine license plates

Automated License Plate Identifier (ALDEN) is a License Plate Recognition (LPR) System developed to recognize images of Philippine license plates. ALDEN captures images of an approaching vehicle when a sufficient distance from the camera is obtained, localizes the license plate from the scene and re...

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Main Authors: Villanueva, Myra Josephine S., Ilao, Joel P., Cervania, Chloe Michelle K., Ku, Vincent Spencer Y., Ragos Ty, Desmond Carvey T.
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Published: Animo Repository 2005
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/3211
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Institution: De La Salle University
id oai:animorepository.dlsu.edu.ph:faculty_research-4190
record_format eprints
spelling oai:animorepository.dlsu.edu.ph:faculty_research-41902022-06-17T06:44:21Z Automated license plate recognition of Philippine license plates Villanueva, Myra Josephine S. Ilao, Joel P. Cervania, Chloe Michelle K. Ku, Vincent Spencer Y. Ragos Ty, Desmond Carvey T. Automated License Plate Identifier (ALDEN) is a License Plate Recognition (LPR) System developed to recognize images of Philippine license plates. ALDEN captures images of an approaching vehicle when a sufficient distance from the camera is obtained, localizes the license plate from the scene and reads its content. This system is designed to be robust against changes in illuminations, and to a limited degree, correct perspective distortions in the acquired images, while still maintaining real-time performances. This paper describes the design and implementation of the ALDEN. Pre-processing techniques are first applied to the acquired raw images to correct uneven illumination, and perspective distortion. The license plate is then extracted from the visual scene, binarized, and segmented into characters using knowledge of the size and locations of characters in a license plate area using the Philippine License Plate format. Character Identification is then performed by segmenting the characters into sixteen regions, and comparing the regions with character templates using correlation as a similarity measure. Performance tests using this technique tested on 300 character images yield an average recognition rate of 93.75 percent. 2005-12-12T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/3211 Faculty Research Work Animo Repository Optical pattern recognition Automobile license plates--Data processing Computer Sciences
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Optical pattern recognition
Automobile license plates--Data processing
Computer Sciences
spellingShingle Optical pattern recognition
Automobile license plates--Data processing
Computer Sciences
Villanueva, Myra Josephine S.
Ilao, Joel P.
Cervania, Chloe Michelle K.
Ku, Vincent Spencer Y.
Ragos Ty, Desmond Carvey T.
Automated license plate recognition of Philippine license plates
description Automated License Plate Identifier (ALDEN) is a License Plate Recognition (LPR) System developed to recognize images of Philippine license plates. ALDEN captures images of an approaching vehicle when a sufficient distance from the camera is obtained, localizes the license plate from the scene and reads its content. This system is designed to be robust against changes in illuminations, and to a limited degree, correct perspective distortions in the acquired images, while still maintaining real-time performances. This paper describes the design and implementation of the ALDEN. Pre-processing techniques are first applied to the acquired raw images to correct uneven illumination, and perspective distortion. The license plate is then extracted from the visual scene, binarized, and segmented into characters using knowledge of the size and locations of characters in a license plate area using the Philippine License Plate format. Character Identification is then performed by segmenting the characters into sixteen regions, and comparing the regions with character templates using correlation as a similarity measure. Performance tests using this technique tested on 300 character images yield an average recognition rate of 93.75 percent.
format text
author Villanueva, Myra Josephine S.
Ilao, Joel P.
Cervania, Chloe Michelle K.
Ku, Vincent Spencer Y.
Ragos Ty, Desmond Carvey T.
author_facet Villanueva, Myra Josephine S.
Ilao, Joel P.
Cervania, Chloe Michelle K.
Ku, Vincent Spencer Y.
Ragos Ty, Desmond Carvey T.
author_sort Villanueva, Myra Josephine S.
title Automated license plate recognition of Philippine license plates
title_short Automated license plate recognition of Philippine license plates
title_full Automated license plate recognition of Philippine license plates
title_fullStr Automated license plate recognition of Philippine license plates
title_full_unstemmed Automated license plate recognition of Philippine license plates
title_sort automated license plate recognition of philippine license plates
publisher Animo Repository
publishDate 2005
url https://animorepository.dlsu.edu.ph/faculty_research/3211
_version_ 1736864171834736640