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Author: Ondrej Martinsky

Affiliation: Brno University of Technology, Faculty of Information Technology, Czech Republic

ISBN: 978-989-8111-37-1

ISSN: 2184-4992

Keyword(s): Machine vision, artificial intelligence, neural networks, optical character recognition, OCR, ANPR.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence and Decision Support Systems ; Enterprise Information Systems ; Human-Computer Interaction ; Industrial Applications of Artificial Intelligence ; Machine Perception: Vision, Speech, Other

Abstract: This work deals with problematic from field of artificial intelligence, machine vision and neural networks in construction of an automatic number plate recognition system (ANPR). This problematic includes mathematical principles and algorithms, which ensure a process of number plate detection, processes of proper characters segmentation, normalization and recognition. Work comparatively deals with methods achieving invariance of systems towards image skew, translations and various light conditions during the capture. Work also contains an implementation of a demonstration model, which is able to proceed these functions over a set of snapshots.

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Paper citation in several formats:
Martinsky, O. (2008). RECOGNITION OF VEHICLE NUMBER PLATES.In Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 6: ICEIS, ISBN 978-989-8111-37-1, pages 136-140. DOI: 10.5220/0001673801360140

@conference{iceis08,
author={Ondrej Martinsky},
title={RECOGNITION OF VEHICLE NUMBER PLATES},
booktitle={Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 6: ICEIS,},
year={2008},
pages={136-140},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001673801360140},
isbn={978-989-8111-37-1},
}

TY - CONF

JO - Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 6: ICEIS,
TI - RECOGNITION OF VEHICLE NUMBER PLATES
SN - 978-989-8111-37-1
AU - Martinsky, O.
PY - 2008
SP - 136
EP - 140
DO - 10.5220/0001673801360140

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