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Authors: Steffen Görmer 1 ; Anton Kummert 1 and Stefan Müller-Schneiders 2

Affiliations: 1 University of Wuppertal, Germany ; 2 Delphi Electronics & Safety, Germany

ISBN: 978-989-8111-69-2

Keyword(s): Traffic sign detection, Color feature extraction, Color segmentation, Color analysis.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Feature Extraction ; Features Extraction ; Image and Video Analysis ; Image Formation and Preprocessing ; Image Formation, Acquisition Devices and Sensors ; Informatics in Control, Automation and Robotics ; Signal Processing, Sensors, Systems Modeling and Control

Abstract: A common approach for traffic sign detection and recognition algorithms is to use shape based and in addition color features. Especially to distinguish between speed-limit and end-of-speed-limit-signs the usage of color information can be helpful as the outer border of speed-signs is in a forceful red. In this paper the focus is faced on color features of speed-limit and no-overtaking signs. The apparent color in the captured image is varying very much due to illumination conditions, sign surface condition and viewing angle. Therefore the color distribution in the HSV color space of a sufficient amount of signs at different illumination conditions and aging has been collected, examined, and a matching mathematical model is developed to describe the subregion in the according color space. Once the color region of traffic signs is known, two kinds of traffic sign segmentation algorithms are developed and evaluated with the explicit focus only on color features to preselect subregions in the image where (red bordered) traffic signs are likely to be. (More)

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Paper citation in several formats:
Görmer S.; Kummert A.; Müller-Schneiders S. and (2009). COLOR FEATURES FOR VISION-BASED TRAFFIC SIGN CANDIDATE DETECTION.In Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009) ISBN 978-989-8111-69-2, pages 107-113. DOI: 10.5220/0001746101070113

@conference{visapp09,
author={Steffen Görmer and Anton Kummert and Stefan Müller{-}Schneiders},
title={COLOR FEATURES FOR VISION-BASED TRAFFIC SIGN CANDIDATE DETECTION},
booktitle={Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)},
year={2009},
pages={107-113},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001746101070113},
isbn={978-989-8111-69-2},
}

TY - CONF

JO - Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)
TI - COLOR FEATURES FOR VISION-BASED TRAFFIC SIGN CANDIDATE DETECTION
SN - 978-989-8111-69-2
AU - Görmer, S.
AU - Kummert, A.
AU - Müller-Schneiders, S.
PY - 2009
SP - 107
EP - 113
DO - 10.5220/0001746101070113

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