Abstract:For the intelligent traffic, there are inaccuracies in the multi-dimensional information identification of vehicles. Especially for vehicle logo recognition, the recognition results depend largely on high-resolution and high-quality images. A new vehicle logo identification method is proposed for distinguishing low-quality vehicle image captured at the bayonet. This method is based on the feature fusion of D-S evidence theory, extracts Hu invariant moments and HOG features, and uses different classifiers,the basic probability distribution (BPA) is constructed, the improved D-S evidence theory is used to fuse, and the final recognition result is given according to the discriminant rule. Through experiments, it is proved that the accuracy can be maintained at a low resolution, and the classification accuracy is 94.29%, which is more robust than a single feature recognition.