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Analysis of EEG Signals and Facial Expressions to Detect Drowsiness and Fatigue using Gabor Filters and SVM Linear Classifier

by N Mohammed Abu Basim, P Sathyabalan, P Suresh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 115 - Number 11
Year of Publication: 2015
Authors: N Mohammed Abu Basim, P Sathyabalan, P Suresh
10.5120/20194-2433

N Mohammed Abu Basim, P Sathyabalan, P Suresh . Analysis of EEG Signals and Facial Expressions to Detect Drowsiness and Fatigue using Gabor Filters and SVM Linear Classifier. International Journal of Computer Applications. 115, 11 ( April 2015), 9-14. DOI=10.5120/20194-2433

@article{ 10.5120/20194-2433,
author = { N Mohammed Abu Basim, P Sathyabalan, P Suresh },
title = { Analysis of EEG Signals and Facial Expressions to Detect Drowsiness and Fatigue using Gabor Filters and SVM Linear Classifier },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 115 },
number = { 11 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 9-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume115/number11/20194-2433/ },
doi = { 10.5120/20194-2433 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:54:32.477127+05:30
%A N Mohammed Abu Basim
%A P Sathyabalan
%A P Suresh
%T Analysis of EEG Signals and Facial Expressions to Detect Drowsiness and Fatigue using Gabor Filters and SVM Linear Classifier
%J International Journal of Computer Applications
%@ 0975-8887
%V 115
%N 11
%P 9-14
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

More sophistication in vehicle's state of art technologies in driver assistance systems and stringent laws implemented by the governments did not stop any of the road accidents in the developing countries like India. The report shows that India contributes nearly 9. 5% of the total 1. 2 million road accidents globally. Among that, nearly 60-70% of road accidents are due to manmade faults like attention-less driving, usage of mobile phones while driving, intoxication of alcohol or any other drugs. The proposed system is designed based on the ground breaking concept known as "humanizing technology" which monitors the physiological changes especially in human brain and facial expressions of the driver and get processed using Gabor filters and SVM linear kernel classifier. The system can crisscross autonomously whether the ignition should get initiated or not. This type of system not only helps the drivers from the accidents, but also a great paradise for pedestrians.

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Index Terms

Computer Science
Information Sciences

Keywords

Driver assistance systems road accidents manmade faults humanizing technology physiological changes facial expressions Gabor filter SVM linear kernel

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