Improving pan-European speed-limit signs recognition with a new 'global number segmentation' before digit recognition
| Autor: | Bargeton, Alexandre, Moutarde, Fabien, Nashashibi, Fawzi, Bradai, Benazouz |
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| Přispěvatelé: | Centre de Robotique (CAOR), Mines Paris - PSL (École nationale supérieure des mines de Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Informatique, Mathématiques et Automatique pour la Route Automatisée (IMARA), Inria Paris-Rocquencourt, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Valeo Driving Assistance Domain, VALEO, MINES ParisTech - École nationale supérieure des mines de Paris |
| Jazyk: | angličtina |
| Rok vydání: | 2008 |
| Předmět: | |
| Zdroj: | IEEE Intelligent Vehicles Symposium (IV'08) IEEE Intelligent Vehicles Symposium (IV'08), Jun 2008, Eindhoven, Netherlands |
| Popis: | International audience; In this paper, we present an improved European speed-limit sign recognition system based on an original “global number segmentation” (inside detected circles) before digit segmentation and recognition. The global speed-limit sign detection and correct recognition rate, currently evaluated on videos recorded on a mix of French and German roads, is around 94 %, with a misclassification rate below 1%, and not a single validated false alarm in several hours of recorded videos. Our greyscale-based system is intrinsically insensitive to colour variability and quite robust to illumination variations, as shown by an on-road evaluation under bad weather conditions (cloudy and rainy) which yielded 84% good detection and recognition rate, and by a first night-time on-road evaluation with 75% correct detection rate. Due to recognition occurring at digit level, our system has the potential to be very easily extended to handle properly all variants of speed-limit signs from various European countries. Regarding computation load, videos with images of 640x480 pixels can be processed in real-time at ~20frames/s on a standard 2.13GHz dual-core laptop. |
| Databáze: | OpenAIRE |
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