Method for vehicle-logo recognition based on principal components analysis and BP neural network

Based on principal component analysis,the vehicle logo recognition algorithm is proposed in this paper,which is on the basis of comparative data dimension reduction methods.Firstly,eigen-vehicle-logos is obtained by using principal component analysis.Secondly,projection coordinates on the eigen-vehicle-logos subspace of the known samples are used as the features of vehicle logo recognition.Finally,according to the projection coordinates of the unknown sample,vehicle logo types are recognized by BP neural network.The practical experiment results show that the proposed method can increase the recognition rate and reduce the computing cost greatly,and it is robust to noises and illumination variation.