Traffic Signs Detection Using Tracking with Prediction

This paper proposes an efficient algorithm for real-time traffic sign detection. The article considers the practicability of using HSV color space to extract the red color. An algorithm to remove noise to improve the accuracy and speed of detection was developed. A modified Generalized Hough transform is then used to detect traffic signs. The current velocity of a vehicle is used to predict the sign's location in the adjacent frames in a video sequence. Finally, the detected objects are being classified. The detection and classification of road signs algorithms are implemented using CUDA and operate in real time on an Android device. The developed algorithms have been tested using real scene images and the German Traffic Sign Detection Benchmark (GTSDB) dataset and showed efficient results.