Vehicle Make Recognition Based on Convolutional Neural Network

Vehicle analysis has been investigated for decades, which involves license plate recognition, intelligent traffic. Among these applications, vehicle make recognition is a challenging task due to the close appearance between car models. In this paper, we propose an architecture to recognize vehicle make based on convolutional neural network (CNN). The moving car is first localized by frame difference, the resultant binary image is used to detect the frontal view of a car by a symmetry filter. The detected frontal view is used to train and test the CNN. Experimental results show that our proposed framework achieves favorable recognition accuracy.