Road-Types Classification using Audio Signal Processing and SVM Method

被引：0
|
作者：
Dogan, Daghan [1 ]
机构：
[1] Tubitak Bilgem, Tasarim Entegrasyon & Dogrulama, PK 74, TR-41470 Gebze, Kocaeli, Turkey
来源：
2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2017年
关键词：
support vector machine (SVM); acustic signal processing; classification;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
In this study, a low-cost system which classifies different road conditions (asphalt, gravel, snowy and stony road) using acoustic signal processing is proposed. Thus it is aimed to estimate road/tire friction forces in the active safety systems. Classical acoustic signal processing methods which are linear predictive coding (LPC), power spectrum (PSC) and mel-frequency cepstrum coefficients (MFCC) are used with minimum variance and maximum distance principle in this system. The classification process is also executed by support vector machine (SVM).
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页数：4
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