DocumentCode
1598754
Title
Classification of moving vehicle using multi-frame time domain features
Author
Paulraj, M.P. ; Adom, Abdul Hamid ; Sundararaj, Sathishkumar
Author_Institution
School of Mechatronic Engineering, Universiti Malaysia Perlis, Ulu Pauh Campus, 02600, Malaysia
fYear
2013
Firstpage
529
Lastpage
533
Abstract
This research work is mainly focused on recognition of different vehicles and its position using acoustic sound source to assist the Differentially Hearing Ability Abled (DHAA). In this paper, a simple protocol has been designed to record the noise emanated by the moving vehicles under different weather conditions and also at different vehicle speed. Two feature extraction methods namely Auto regressive and statistical feature methods are used to extract the features from the recorded acoustic signature. The Radial Basis Function Network (RBFN) model was used for classification. The networks effectiveness has been validated through stimulation.
Keywords
Accuracy; Biology; Auto Regressive Model; Differentially Hearing Ability Abled (DHAA); Radial Basis Function Network (RBFN); Statistical Features;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems and Control (ISCO), 2013 7th International Conference on
Conference_Location
Coimbatore, Tamil Nadu, India
Print_ISBN
978-1-4673-4359-6
Type
conf
DOI
10.1109/ISCO.2013.6481211
Filename
6481211
Link To Document