An automatic image recognition system for winter road surface condition classification

This paper investigates the feasibility of classifying winter road surface conditions using images from low cost cameras mounted on regular vehicles. RGB features along with gradients have been used as feature vectors. A Support Vector Machine (SVM) is trained using the extracted features and then used to classify the images into their respective categories. Different training schemes and their effect on the classification rate are also discussed along with the possibility of developing an automated winter road surface classification system in future.