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18 November 2015 Exploiting automatically generated databases of traffic signs and road markings for contextual co-occurrence analysis
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Combined databases of road markings and traffic signs provide a complete and full description of the present traffic legislation and instructions. Such databases contribute to efficient signage maintenance, improve navigation, and benefit autonomous driving vehicles. A system is presented for the automated creation of such combined databases, which additionally investigates the benefit of this combination for automated contextual placement analysis. This analysis involves verification of the co-occurrence of traffic signs and road markings to retrieve a list of potentially incorrectly signaled (and thus potentially unsafe) road situations. This co-occurrence verification is specifically explored for both pedestrian crossings and yield situations. Evaluations on 420 km of road have shown that individual detection of traffic signs and road markings denoting these road situations can be performed with accuracies of 98% and 85%, respectively. Combining both approaches shows that over 95% of the pedestrian crossings and give-way situations can be identified. An exploration toward additional co-occurrence analysis of signs and markings shows that inconsistently signaled situations can successfully be extracted, such that specific safety actions can be directed toward cases lacking signs or markings, while most consistently signaled situations can be omitted from this analysis.
© 2015 SPIE and IS&T 1017-9909/2015/$25.00 © 2015 SPIE and IS&T
Lykele Hazelhoff, Ivo M. Creusen, Thomas Woudsma, and Peter H. N. de With "Exploiting automatically generated databases of traffic signs and road markings for contextual co-occurrence analysis," Journal of Electronic Imaging 24(6), 061203 (18 November 2015).
Published: 18 November 2015


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