基于深度学习的车标识别方法研究

对交通监控录像中车牌污损、遮挡的肇事车辆信息进行确认是现阶段智能交通系统中的一个重要问题,车标作为一个关键特征,可以起到辅助判别的作用.提出了一种基于深度学习的车标识别方法,相对于以人工提取特征为主的传统车标识别方法,该方法具有可自主学习特征、可直接输入图像等优点.实验表明,这种方法正确率较高,在光照变化和噪声污染下的准确性和稳定性较好,能够有效降低车标识别的错误率.

Vehicle Logo Recognition Based on Deep Learning

Identification of vehicles which have caused traffic accidents is an important issue in intelligent transportation system (ITS).However,due to the missing or the stains on the car license plates,it is difficult to locate the vehicles.Logos,as key features of vehicles,can also help to identify vehicles of interest.This paper proposed a method to detect and recognize vehicle logos based on deep learning.Compared with traditional approaches that extract features manually,this method uses original images as inputs to learn features automatically.Experimental results demonstrate that the proposed method has a high accuracy,and even in the conditions of illumination change and noise contamination,it is able to produce stable and accurate results.