Speed Detection and Diagnosis of Symptoms by Using Color and Shape Information

Color and shape are basic characteristics which are used to recognize traffic signs. In this paper, a new speed limit sign detection method in various conditions is proposed. In this method, color image is segmented based on a thresholding technique in HSI color space. Then, corner features are detected using convolution masks and found the location of sign. The first advantage of this method is high accuracy to detect the location of sign. So, the object can be detected with 30% noise level, 30 meters for distances of signs, and for rotated signs. The second advantage of the proposed method is high speed in sign detection. Utimately, the type of sign can be recognized with eliminate redundant information and match between extracted image and database image. If the illumination conditions be ideal, the recognition rate is obtained to 89%.