JOURNAL ARTICLE

Acoustic signal based feature extraction for vehicular classification

Abstract

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.

Keywords:
Feature extraction Centroid Computer science Entropy (arrow of time) Pattern recognition (psychology) SIGNAL (programming language) Speech recognition Energy (signal processing) Artificial intelligence Feature (linguistics) Noise (video) Acoustics Mathematics Physics Statistics

Metrics

15
Cited By
1.10
FWCI (Field Weighted Citation Impact)
11
Refs
0.82
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Autonomous Vehicle Technology and Safety
Physical Sciences →  Engineering →  Automotive Engineering
Vehicle Noise and Vibration Control
Physical Sciences →  Engineering →  Automotive Engineering
Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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