A 2DLDA Based Algorithm for Real Time Vehicle Type Recognition

Abstract

Vehicle type recognition generally refers to identifying the make and model of vehicles through collected images or other information. This paper presents a Two-Dimensional Linear Discriminant Analysis (2DLDA) based algorithm for real time vehicle type recognition. The algorithm is initiated by extracting a region of interest (ROI) relative to the located license plate, and then robust features obtained by performing 2DLDA on the gradients of ROI are used for recognition. Experimental results show that the algorithm can achieve high recognition accuracy (94.7%) and that it is not sensitive to variations of vehicle colors and light conditions. The computational complexity is low so that the algorithm can be implanted in real time.