Indian Traffic Sign Detection and Recognition

Traffic Sign Recognition system is a very significant part of the Intelligent Transportation System, as traffic signs assist the drivers to drive more carefully and professionally. The main aim of this work is to present an efficient approach for detection and recognition of Indian traffic signs. Information regarding color and geometrical shape of traffic signs are utilized by the system for localizing the traffic sign in the acquired image. An RGB color saliency attention model of traffic sign makes use of an algorithm, which discriminates the sign candidate from other objects. Morphological shape filter is exploited for extracting the geometrical information of the traffic sign. Nearest neighbor matching-based recognition is performed between localized candidate features and stored Indian traffic sign database (ITSD) features. Speed up robust features (SURF) of a traffic sign is used in nearest neighbor matching to find out the resemblance between the traffic signs. System robustness is cross-examined for illumination, scale, rotation variations, similar color and shape variations, a standard data set is also considered to evaluate the system performance. The simulation results illustrate that the proposed system is working effectively under various hazardous condition.