Vehicle Recognition Based on Region Growth of Relative Tension and Similarity Measurement of Side Projection Profile of Vehicle Body

Abstract

Current vehicle recognition methods are less concerned simultaneously with: (1) the scale difference between vehicles and other objects in urban city; and (2) the impact of physical characteristics of vehicles. Based on the region growth of relative tension, a method for measuring the similarity of side projection profile of a vehicle’s body is proposed for recognizing vehicles. First, region growth of relative tension is used to divide 3D point clouds into a series of spatial regions. Point clouds in these regions are projected to a 2D plane. Then, relevant 2D features are extracted, including side projection profile of vehicle body and sizes of vehicles. Screening by these relevant features, part of these regions, and point clouds inside them which conforms to the similarity measurement conditions of vehicles are selected. Quantitative evaluations on the selected data set show that the proposed algorithm achieves a recall, precision, and F-score of 0.837, 0.979, and 0.902, respectively, in recognizing vehicles. Comparative studies demonstrate the superior performance of the proposed algorithm.