Application Research of Neural Network in Vehicle Target Recognition and Classification

Based on the learning theory of neural network, this paper makes a thorough study on the recognition method of vehicle information, and puts forward a feasible solution to the feature extraction of vehicle image and the recognition of vehicle classification. Firstly, the outline features of the whole or part of the vehicle image are discussed and analyzed. By transforming the distance features, relative value of absolute distance is determined as the input data of the vehicle recognition feature of this paper, and as the neural network classifier. Then, K-means clustering algorithm is used to get the feature centers of the vehicle type, which can be used to distinguish the following vehicles and get the shape classification results of the vehicle. Finally, network training, network testing and vehicle identification are carried out, and the experimental results are analyzed. The experimental results show that this method can acquire vehicle features adaptively, so it can be applied to multiple kinds of scenarios.