Image analysis algorithms for vehicle color recognition

This work discusses about the implementation of a vehicle color recognition system to be used with the vehicle license plate recognition system. Because of the complexity of Thai alphabet, current license plate recognition system fails in correctly recognizing vehicles that have the same number but different Thai characters. Also the current system cannot identify illegal number plates that are being used. This color recognition system will help to resolve these problems and increase the accuracy of the vehicle recognition system. In addition, this system will provide a wide range of color classification which includes 13 colors including white, silver and gray colors. Color recognition is done by two methods: one with machine learning and one without machine learning. A best accuracy of 87.52% is given when using SVM to classify colors.