Road snow and rain state automatic identification method based on feature information classification

A road snow and rain state automatic identification method based on feature information classification comprises a step A of extracting a sample describing feature and constructing a Bayes classifier, and a step B of detecting the road state. The step A comprises a small step A 1 of acquiring a sample image, a small step A 2 of preprocessing the image, a small step A 3 of extracting a sampling image texture attribute value and an average gray value of a road effective coverage sample, a small step A 4 of calculating a probability density function of the road sample, and a small step A 5 of determining an operational rule of a type conditional probability density function to construct the Bayes classifier. The step B comprises a small step B 1 of acquiring a road detecting image, a small step B 2 of preprocessing the image, a small step B 3 of extracting a texture attribute value and an average gray value of a road detecting standard image frame, and a small step B 4 of judging the road surface state of the road. The road snow and rain state automatic identification method based on the feature information classification can adapt to various weather variations and complexity and changes of traffic road states, detection efficiency and accuracy are high, and cost is low, so that the road snow and rain state automatic identification method based on the feature information classification provides reference for traffic safety guarantee and traffic management.