Real-time recognition of U.S. speed signs

Abstract

In this paper a camera-based system for detection, tracking, and classification of U.S. speed signs is presented. The implemented application uses multiple connected stages and iteratively reduces the number of pixels to process for recognition. Possible sign locations are detected using a fast, shape-based interest operator. Remaining objects other than speed signs are discarded using a classifier similar to the Viola-Jones detector. Classification results from tracked candidates are utilized to improve recognition accuracy. On a standard PC the system reached a detection speed of 27 fps with an accuracy of 98.8%. Including classification, speed sign recognition rates of 96.3% were achieved with a frame rate of approximately 11 fps and one false alarm every 42 s.