Authors:
Steffen Görmer
1
;
Anton Kummert
1
and
Stefan Müller-Schneiders
2
Affiliations:
1
University of Wuppertal, Germany
;
2
Delphi Electronics & Safety, Germany
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 i
n the image where (red bordered) traffic signs are likely to be.
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