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Authors: Jack Greenhalgh and Majid Mirmehdi

Affiliation: University of Bristol, United Kingdom

Keyword(s): Computer Vision, Machine Learning, Text Recognition, Intelligent Transportation Systems.

Related Ontology Subjects/Areas/Topics: Applications ; Classification ; Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Image Understanding ; Pattern Recognition ; Software Engineering ; Theory and Methods ; Video Analysis

Abstract: A method for the automatic detection and recognition of text and symbols painted on the road surface is presented. Candidate regions are detected as maximally stable extremal regions (MSER) in a frame which has been transformed into an inverse perspective mapping (IPM) image, showing the road surface with the effects of perspective distortion removed. Detected candidates are then sorted into words and symbols, before they are interpreted using separate recognition stages. Symbol-based road markings are recognised using histogram of oriented gradient (HOG) features and support vector machines (SVM). Text-based road signs are recognised using a third-party optical character recognition (OCR) package, after application of a perspective correction stage. Matching of regions between frames, and temporal fusion of results is used to improve performance. The proposed method is validated using a data-set of videos, and achieves F-measures of 0.85 for text characters and 0.91 for symbols.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Greenhalgh, J. and Mirmehdi, M. (2015). Detection and Recognition of Painted Road Surface Markings. In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM; ISBN 978-989-758-076-5; ISSN 2184-4313, SciTePress, pages 130-138. DOI: 10.5220/0005273501300138

@conference{icpram15,
author={Jack Greenhalgh. and Majid Mirmehdi.},
title={Detection and Recognition of Painted Road Surface Markings},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM},
year={2015},
pages={130-138},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005273501300138},
isbn={978-989-758-076-5},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM
TI - Detection and Recognition of Painted Road Surface Markings
SN - 978-989-758-076-5
IS - 2184-4313
AU - Greenhalgh, J.
AU - Mirmehdi, M.
PY - 2015
SP - 130
EP - 138
DO - 10.5220/0005273501300138
PB - SciTePress