Acoustic signal based feature extraction for vehicular classification

Acoustic signal classification consists of extracting the features from a sound, and of using these features to identify classes the sound is liable to fit.. Different types of noise coming from different vehicles mix in the environment and identifying a particular vehicle is a challenging one. Feat...

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Bibliographic Details
Published in:2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE) Vol. 2; pp. V2-11 - V2-14
Main Authors: Padmavathi, G, Shanmugapriya, D, Kalaivani, M
Format: Conference Proceeding
Language:English
Published: IEEE 01.08.2010
Subjects:
Entropy
Feature extraction
Noise
Short Time Energy
Spectral Centroid
Spectral Flux
Spectral Rolloff
Vehicle acoustic signal
Vehicles
Zero-Crossing Rate
ISBN:1424465397, 9781424465392
ISSN:2154-7491
Online Access:Get full text
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Summary:Acoustic signal classification consists of extracting the features from a sound, and of using these features to identify classes the sound is liable to fit.. Different types of noise coming from different vehicles mix in the environment and identifying a particular vehicle is a challenging one. Feature Extraction is done to identify the characteristic of the vehicle. The characteristic of each vehicle will be used to detect its presence and classify its type. Six different features of the vehicle acoustic signals are calculated and then further utilized as input to the classification system. These features include Signal Energy, Energy Entropy, Zero-Crossing Rate, Spectral Roll-Off, Spectral Centroid and Spectral Flux. All these features are extracted from each and every acoustic signal of the vehicles.
ISBN:1424465397
9781424465392
ISSN:2154-7491
DOI:10.1109/ICACTE.2010.5579804