AUTOMATIC RECOGNITION OF ROAD SIGNS IN DIGITAL IMAGES FOR GIS UPDATE

André R. S. Marçal, Isabel R. Gonçalves

Abstract

A method for automatic recognition of road signs identified in digital video images is proposed. The method is based on features extracted from cumulative histograms and supervised classification. The training of the classifier is done with a small number of images (1 to 6) from each sign type. A practical experiment with 260 images and 26 different road sign was carried out. The average classification accuracy of the method with the standard settings was found to be 93.6%. The classification accuracy is improved to 96.2% by accepting the sign types ranked 1st and 2nd by the classifier, and to 97.4% by also accepting the sign type ranked 3rd. These results indicate that this can be a valuable tool to assist Geographic Information System (GIS) updating process based on Mobile Mapping System (MMS) data.

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Paper Citation


in Harvard Style

R. S. Marçal A. and R. Gonçalves I. (2009). AUTOMATIC RECOGNITION OF ROAD SIGNS IN DIGITAL IMAGES FOR GIS UPDATE . In Proceedings of the First International Conference on Computer Imaging Theory and Applications - Volume 1: IMAGAPP, (VISIGRAPP 2009) ISBN 978-989-8111-68-5, pages 129-134. DOI: 10.5220/0001790301290134


in Bibtex Style

@conference{imagapp09,
author={André R. S. Marçal and Isabel R. Gonçalves},
title={AUTOMATIC RECOGNITION OF ROAD SIGNS IN DIGITAL IMAGES FOR GIS UPDATE},
booktitle={Proceedings of the First International Conference on Computer Imaging Theory and Applications - Volume 1: IMAGAPP, (VISIGRAPP 2009)},
year={2009},
pages={129-134},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001790301290134},
isbn={978-989-8111-68-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Computer Imaging Theory and Applications - Volume 1: IMAGAPP, (VISIGRAPP 2009)
TI - AUTOMATIC RECOGNITION OF ROAD SIGNS IN DIGITAL IMAGES FOR GIS UPDATE
SN - 978-989-8111-68-5
AU - R. S. Marçal A.
AU - R. Gonçalves I.
PY - 2009
SP - 129
EP - 134
DO - 10.5220/0001790301290134