Vehicle color recognition based on multiple classifier combination for Intelligent Transportation System

Vehicle information recognition is a key component of intelligent transportation systems. To satisfy vehicle color recognition for traffic enforcement camera system, we propose a method of vehicle color recognition based on multiple classifier combination. Firstly, color type is defined based on human eye sensation, and then suitable color space and classification algorithms are adopted via statistical of large vehicle samples. For distinguished vehicle color types, support vector machine algorithms are used for classification. After generating prior probability and class conditional probability, maximum posterior probability is computed based on Bayes classifier to identify color types for less-distinguishable colors type. At Last support vector machine and Bayes classifier are combined to form a decision tree, which is then simplified to binary classifier problem. Experiment results show good identification of color types, and the total recognition rate is above 85%.