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Western Kentucky University

Real Time Driver Safety System

Abstract

dc:description.abstract

The technology for driver safety has been developed in many fields such as airbag system, Anti-lock Braking System or ABS, ultrasonic warning system, and others. Recently, some of the automobile companies have introduced a new feature of driver safety systems. This new system is to make the car slower if it finds a driver’s drowsy eyes. For instance, Toyota Motor Corporation announced that it has given its pre-crash safety system the ability to determine whether a driver’s eyes are properly open with an eye monitor. This paper is focusing on finding a driver’s drowsy eyes by using face detection technology. The human face is a dynamic object and has a high degree of variability; that is why face detection is considered a difficult problem in computer vision. Even with the difficulty of this problem, scientists and computer programmers have developed and improved the face detection technologies. This paper also introduces some algorithms to find faces or eyes and compares algorithm’s characteristics. Once we find a face in a sequence of images, the matter is to find drowsy eyes in the driver safety system. This system can slow a car or alert the user not to sleep; that is the purpose of the pre-crash safety system. This paper introduces the VeriLook SDK, which is used for finding a driver’s face in the real time driver safety system. With several experiments, this paper also introduces a new way to find drowsy eyes by AOI,Area of Interest. This algorithm improves the speed of finding drowsy eyes and the consumption of memory use without using any object classification methods or matching eye templates. Moreover, this system has a higher accuracy of classification than others.

Degree

thesis:*
Name thesis:degree_name
Master of Computer Science
Discipline thesis:degree_discipline
Department of Mathematics and Computer Science
Year
2009

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Cho, Gyuchoon
Contributors dc:contributor
  • Dr. Ahmed Emam (Director),Dr. Art Shindhelm,Dr. Mustafa Atici

Subjects

dc:subject × 6

Identifiers

dc:identifier.*
Repository record dc:identifier
https://digitalcommons.wku.edu/theses/63
OAI identifier oai:identifier
oai:digitalcommons.wku.edu:theses-1065

Chain of custody

source
Harvested from
Western Kentucky University
Base URL
digitalcommons.wku.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Cho, Gyuchoon. Real Time Driver Safety System. 2009. https://digitalcommons.wku.edu/theses/63