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Traffic sign recognition for unmanned vehicle control

Havur, Mehmet Bülent
In this thesis, video frames acquired by a camera in a moving car are processed for detection of candidates of triangular, rectangular and circular traffic/road signs based on mainly shape information by performing contour analysis. Color information is utilized as an auxiliary method to improve detection. Then recognition based on template matching is realized on detected traffic/road sign candidates. Detection and recognition results of traffic/road signs in video frames taken in different time intervals of day for these methods are compared. After implementation, results show that the video scene taken in a sunny day in the afternoon gives better results than others. Binary threshold plays a great role in detection with respect to Canny edge detector especially for triangular and rectangular traffic signs. Higher number of binary threshold levels improves detection in general. In addition, the recognition rate for triangular and rectangular traffic/road signs is higher than that of circular sings in general by the methods used in this study.