Study for vehicle recognition and classification based on Gabor wavelets transform & HMM

Vehicle recognition and classification is an important part of intelligent transportation system. Now, the technology of vehicle recognition has becoming a hot topic all over the world. A vehicle recognition algorithm based on Gabor wavelets transform and hidden Markov model (HMM) is proposed. A Gabor filters are applied on the vehicle images to construct a group of vectors called nodes, and then feature nodes are derived by using principal component analysis, which decrease the dimension of each node. The image including feature nodes is called Gabor-Vehicle. A set of images representing different instances of the same vehicle are used to train each HMM, and each individual in the database is represented by an optional HMM vehicle model. Experimental results show that the proposed algorithm has a high recognition rate with relatively low complexity.