Detection and recognition of traffic signs using Gabor filters

The paper proposes a three steps algorithm that automatically detects, classifies and recognizes traffic signs from images taken from a car running along European road. Traffic signs are detected by analyzing the color information contained in the images using HSV color space. Detected signs are then classified using correlation with standard sign shapes. The recognition step uses the minimum distance classification based on calculating the Euclidean distance between two feature vectors composed using a Gabor filter with different parameters.