基于音频特征分析的车辆识别软件实现

发布时间：2018-06-02 15:49

本文选题：音频特征 + 高斯混合模型　；参考：《电子科技大学》2014年硕士论文

【摘要】：要大力实现交通运输系统的智能化,智能交通运输系统的发展至关重要,其关键在于车辆的检测及识别。而目前所使用的主流检测方法,由于种种原因,尚难以满足沿道路大量设置的要求,因此,本文以车辆静止或行驶时产生的音频信号为基础,主要对车辆音频信号的特征进行分析,在此基础上提出基于车辆音频信号对车型进行识别的方案的理论研究,并进行初步识别。(1)阐述软件开发的系统总体设计方案,详细描述系统整体的软件架构,主要介绍系统设计中涉及到的音频特征提取模块和基于音频特征的车辆识别模块设计思路,并介绍系统的数据库构成。(2)主要完成音频特征提取模块的详细设计。首先探讨音频去噪方法,为了提高算法对不同信噪比的带噪音频的处理能力,结合维纳滤波和自适应滤波的优势,对谱减法进行改进;其次针对本文所设计的系统平台,为保证系统识别性能,充分考虑音频帧内和帧间的信息,探讨选择Mel倒谱与一阶差分Mel倒谱作为特征参数,在一定程度上提高系统的稳健性。(3)主要探讨识别模型的设计方面,深入研究概率模型中的高斯混合模型方法,GMM不仅能利用到音频信号的时序动态信息,端点检测的精度对其识别性能的影响也很小,设计实现基于GMM的车型识别方法。(4)对前述各章中设计的软件功能和检索算法分别进行了试验测试和软件测试,进行了仿真实验,并得出了相关结论。
[Abstract]:In order to realize the intelligence of transportation system, the development of intelligent transportation system is very important, and the key lies in the detection and identification of vehicles. However, the mainstream detection methods used at present are still difficult to meet the requirements of a large number of settings along the road due to various reasons. Therefore, this paper is based on the audio signals produced by vehicles at rest or driving. Based on the analysis of the characteristics of the vehicle audio signal, this paper puts forward the theoretical research of the vehicle model recognition based on the vehicle audio signal, and describes the overall system design scheme of the software development. The software architecture of the whole system is described in detail. The design ideas of audio feature extraction module and vehicle recognition module based on audio feature are introduced. This paper introduces the database structure of the system. It mainly designs the audio feature extraction module. In order to improve the processing ability of the algorithm with different SNR, combining the advantages of Wiener filter and adaptive filter, the spectral subtraction method is improved. In order to ensure the recognition performance of the system, the information in and between the audio frames is fully considered, and the Mel cepstrum and the first-order differential Mel cepstrum are discussed as the feature parameters. In order to improve the robustness of the system to some extent, the design of the recognition model is mainly discussed. The Gao Si hybrid model method in probabilistic model can not only make use of the timing dynamic information of audio signal, but also have little effect on the performance of endpoint detection. The design and implementation of the vehicle recognition method based on GMM. 4) the software function and retrieval algorithm designed in the above chapters are tested and tested respectively, and the simulation experiments are carried out, and the relevant conclusions are obtained.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN912.34;TP311.52

【参考文献】