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基于频谱分析与支持向量机的车型音频识别研究
引用本文:马侠霖,蔡铭,丁建立.基于频谱分析与支持向量机的车型音频识别研究[J].应用声学,2014,33(4):371-376.
作者姓名:马侠霖  蔡铭  丁建立
作者单位:中山大学工学院 广东省智能交通系统重点实验室,中山大学工学院 广东省智能交通系统重点实验室,中国民航大学中国民航信息技术科研基地
基金项目:国家自然科学基金项目(面上项目,重点项目,重大项目)
摘    要:机动车车型识别是城市道路交通流监测统计的一个重要方面。本文基于频谱分析与支持向量机方法提出一种车型音频识别方法,以1/3倍频程频谱数据作为特征数据,并使用支持向量机方法完成不同车型分类下的车型识别,同时还分析比较了不同训练样本量及不同单个样本数据量大小对识别结果的影响。在将车型细分的情况下,对小汽车、大型公交车、水泥车、摩托车四种车型的样本外识别结果达到96.9%的准确率,验证了方法的有效性。

关 键 词:车型识别  频谱分析  支持向量机  音频信号
收稿时间:7/8/2013 12:00:00 AM
修稿时间:2014/6/28 0:00:00

Audio identification of vehicle type based on frequency analysis and support vector machine
MA Xia-lin,CAI Ming and DING Jian-li.Audio identification of vehicle type based on frequency analysis and support vector machine[J].Applied Acoustics,2014,33(4):371-376.
Authors:MA Xia-lin  CAI Ming and DING Jian-li
Institution:School of Engineering Sun Yat-sen University,Guangdong Provincial Key Laboratory of Intelligent Transportation System,School of Engineering Sun Yat-sen University,Guangdong Provincial Key Laboratory of Intelligent Transportation System,Information Technology Research Base of Civil Aviation Administration of China,Civil Aviation University of China
Abstract:Identification of vehicle type is the important content of the monitoring and statics of urban road traffic flow. This article presents an audio identification method of vehicle type based on frequency analysis and support vector machine (SVM). Researches begin by exacting features as 1/3 octave spectrum data, which are then trained and classified by utilizing SVM classifier. Thereafter accuracy rates under various parameters such as number of training samples and size of single sample will be analyzed and compared. An Out-of-Sample accuracy rate of 96.9% is achieved among 4 different types, which are car, heavy bus, cement truck and motorcycle.
Keywords:Vehicle type identification  Frequency analysis  Support vector machine  Audio signal
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