Mutation Detection System for Actualizing Traffic Sign Inventories

Lykele Hazelhoff, Ivo Creusen, Peter H. N. de With

2014

Abstract

Road safety is influenced by the adequate placement of traffic signs. As the visibility of road signs degrades over time due to e.g. aging, vandalism or vegetation coverage, sign maintenance is required to preserve a high road safety. This is commonly performed based on inventories of traffic signs, which should be conducted periodically, as road situations may change and the visibility of signs degrades over time. These inventories are created efficiently from street-level images by (semi-)automatic road sign recognition systems, employing computer vision techniques for sign detection and classification. Instead of periodically repeating the complete surveying process, these automated sign recognition systems enable re-identification of the previously found signs. This results in the highlighting of changed situations, enabling specific manual validation of these cases. This paper presents a mutation detection approach for semi-automatic updating of traffic sign inventories, together with a case study to assess the practical usability of such an approach. Our system re-identifies 94.8% of the unchanged signs, thereby resulting in a significant reduction of the manual effort required for the semi-automated actualization of the inventory. As the amount of changes equals to 16:9% of the already existing signs, this study also clearly shows the economic relevance and usefulness of periodic updating road sign surveys.

Paper Citation

in Harvard Style

Hazelhoff L., Creusen I. and de With P. (2014). Mutation Detection System for Actualizing Traffic Sign Inventories . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: PANORAMA, (VISIGRAPP 2014) ISBN 978-989-758-004-8, pages 705-713. DOI: 10.5220/0004793707050713

in Bibtex Style

@conference{panorama14,
author={Lykele Hazelhoff and Ivo Creusen and Peter H. N. de With},
title={Mutation Detection System for Actualizing Traffic Sign Inventories},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: PANORAMA, (VISIGRAPP 2014)},
year={2014},
pages={705-713},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004793707050713},
isbn={978-989-758-004-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: PANORAMA, (VISIGRAPP 2014)
TI - Mutation Detection System for Actualizing Traffic Sign Inventories
SN - 978-989-758-004-8
AU - Hazelhoff L.
AU - Creusen I.
AU - de With P.
PY - 2014
SP - 705
EP - 713
DO - 10.5220/0004793707050713