Most of the systems either detect (classify vehicle or background) or classify vehicles in categories such as cars, trucks, buses etc. Unfortunately, there is not too much research on vehicle view classification. This paper presents a classification system of vehicle’s front and back. This system consists of two main phases: feature extraction phase and classification phase. In the first phase, we used two descriptors: HOG (Histogram of Oriented Gradient) and LBP (Local Binary Patterns). In the second phase, we used two types of classifiers SVM (Support Vector Machine) and kNN (k Nearest-Neighbor). The experimental results reveal that the system can recognize robustly the views of the vehicles. The system was tested using Matlab. The accuracy of the system is about 97,47%.
