Automatic vehicle identfication for Argentinean license plates using intelligent template matching

The problem of automatic number plate recognition (ANPR) has been studied from different aspects since the early 90s. Efficient approaches have been recently developed, particularly based on the features of the license plate representation used in different countries. This paper focuses on a novel a...

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Bibliographic Details
Authors: Gazcón, Nicolás Fernando, Chesñevar, Carlos Iván, Castro, Silvia Mabel
Format: article
Status:Published version
Publication Date:2012
Country:Argentina
Institution:Consejo Nacional de Investigaciones Científicas y Técnicas
Repository:CONICET Digital (CONICET)
Language:English
OAI Identifier:oai:ri.conicet.gov.ar:11336/195819
Online Access:http://hdl.handle.net/11336/195819
Access Level:Open access
Keyword:LICENSE PLATE RECOGNITION
TEMPLATE RECOGNITION
IMAGE PROCESSING
https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
Description
Summary:The problem of automatic number plate recognition (ANPR) has been studied from different aspects since the early 90s. Efficient approaches have been recently developed, particularly based on the features of the license plate representation used in different countries. This paper focuses on a novel approach to solving the ANPR problem for Argentinean license plates, called Intelligent Template Matching (ITM). We compare the performance obtained with other competitive approaches to robust pattern recognition (such as artificial neural networks), showing the advantages both in classification accuracy and training time. The approach can also be easily extended to other license plate representation systems different from the one used in Argentina.