Traffic sign recognition in color image sequences
- 2 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
At the Daimler-Benz Research Center in Ulm a system for traffic sign recognition is under development. The task of the system is to detect and interpret traffic signs in colour image sequences; these images are acquired by a camera mounted in a car. The color segmentation of the incoming images is performed with a high order neural network. Based on this color segmented images and using a priori knowledge, hypotheses on image regions containing traffic signs are generated. The kind of traffic sign is also hypothesized. The preselected image regions are further analysed in order to verify or reject the hypothesis. The analysis finally interprets the contents of the traffic signs. The control of the analysis is supported by knowledge on traffic signs and outdoor scenes in general. The whole knowledge is stored in a framebased network.<>Keywords
This publication has 6 references indexed in Scilit:
- Colour segmentation with polynomial classificationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- One-pass encoding of connected components in multivalued imagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- FRM: Ein Frame-Repräsentationsmodell und seine formale SemantikInformatik-Fachberichte, 1989
- An Overview of the KL‐ONE Knowledge Representation System*Cognitive Science, 1985
- Darstellung und Nutzung von Expertenwissen für ein BildanalysesystemInformatik-Fachberichte, 1985
- Pattern AnalysisPublished by Springer Nature ,1981