Vehicle Type Classification using Hierarchical Classifiers

Abstract

Vehicle type classification based on images is widely applied in traffic surveillance and monitoring system. It has been used in billing at toll collection stations and preventing heavy trucks from entering city viaducts. A hierarchical vehicle detection and classification system is proposed in this paper. A cascade ensemble classifier, accepting Multiple Layer Perceptron (MLP) and K-Nearest Neighbor (K-NN) as base classifiers, is proposed for the vehicle type classification. The experiments are conducted, and the hierarchical classifier with two layers offers a reliability of 97.8% with a rejection rate of 3.0%, which show the effectiveness of our proposed hierarchical vehicle detection and classification system.