Paper
27 January 1998 Localization and recognition of traffic signs for automated vehicle control systems
Mahmoud M. Zadeh, T. Kasvand, Ching Y. Suen
Author Affiliations +
Proceedings Volume 3207, Intelligent Transportation Systems; (1998) https://doi.org/10.1117/12.300865
Event: Intelligent Systems and Advanced Manufacturing, 1997, Pittsburgh, PA, United States
Abstract
We present a computer vision system for detection and recognition of traffic signs. Such systems are required to assist drivers and for guidance and control of autonomous vehicles on roads and city streets. For experiments we use sequences of digitized photographs and off-line analysis. The system contains four stages. First, region segmentation based on color pixel classification called SRSM. SRSM limits the search to regions of interest in the scene. Second, we use edge tracing to find parts of outer edges of signs which are circular or straight, corresponding to the geometrical shapes of traffic signs. The third step is geometrical analysis of the outer edge and preliminary recognition of each candidate region, which may be a potential traffic sign. The final step in recognition uses color combinations within each region and model matching. This system maybe used for recognition of other types of objects, provided that the geometrical shape and color content remain reasonably constant. The method is reliable, easy to implement, and fast, This differs form the road signs recognition method in the PROMETEUS. The overall structure of the approach is sketched.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mahmoud M. Zadeh, T. Kasvand, and Ching Y. Suen "Localization and recognition of traffic signs for automated vehicle control systems", Proc. SPIE 3207, Intelligent Transportation Systems, (27 January 1998); https://doi.org/10.1117/12.300865
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KEYWORDS
Control systems

Vehicle control

Computing systems

Roads

Computer vision technology

Image segmentation

Machine vision

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