关键词: 车辆识别, 进化优化, 对称测度

Abstract: A real-time vehicle detection and recognition system based on the fusion of data from radar and a video sensor is presented.The radar data is used both for narrowing down the size of the search area for vehicle rears on the video image and for the distance measurement of the vehicles in front.Using the video sensor a radar object is verified and the width as well as the lateral position of the vehicle are determined.The contribution of this work is threefold：At first，a methodology for developing a novel evolutionary optimized symmetry measure is proposed.Secondly，a vehicle detection and recognition algorithm is demonstrated，which consists of two steps：Hypothesis generation using a detector based on a set of Haar-like filters and an AdaBoost learning algorithm and hypothesis verification using an evolutionary optimized and biologically motivated vehicle recognition system.Finally，the performance of the system is evaluated by not only using classical confusion matrices but also giving information on the accuracy of the width and lateral position sensing.Experimental results demonstrate a robust and real-time system trained and tested on more than 30 000 images.

Key words: vehicle recognition, evolutionary optimized, symmetry measurement