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We present a new modular traffic signs recognition system, successfullyapplied to both American and European speed limit signs. Our sign detectionstep is based only on shape-detection (rectangles or circles). This enables itto work on grayscale images, contrary to most European competitors, which easesrobustness to illumination conditions (notably night operation). Speed signcandidates are classified (or rejected) by segmenting potential digits insidethem (which is rather original and has several advantages), and then applying aneural digit recognition. The global detection rate is ~90% for both (standard)U.S. and E.U. speed signs, with a misclassification rate <1%, and no validatedfalse alarm in >150 minutes of video. The system processes in real-time ~20frames/s on a standard high-end laptop.

Modular Traffic Sign Recognition applied to on-vehicle real-time visual detection of American and European speed limit signs