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Drowsiness detection for car assisted driver system using image processing analysis

Ani Syazana, Jasni (2010) Drowsiness detection for car assisted driver system using image processing analysis. Faculty Of Electrical & Electronic Engineering, Universiti Malaysia Pahang.

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Drowsiness detection for car assisted driver system using image processing analysis - Table of content.pdf - Accepted Version

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PDF (Abstract)
Drowsiness detection for car assisted driver system using image processing analysis - Abstract.pdf - Accepted Version

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Drowsiness detection for car assisted driver system using image processing analysis - Chapter 1.pdf - Accepted Version

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Drowsiness detection for car assisted driver system using image processing analysis - References.pdf - Accepted Version

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Abstract

The current technology in digital computer system allows researchers around the world to study the fatigue behavior. Although the current technology of drowsiness detector has been created, it is lack of efficient since the detection is used ordinary sensor. This project is to develop a driver drowsiness detection system by using histogram analysis. It is known that a driver is under drowsiness influences by looking at the eyelid. Based on the previous research, there is none used histogram for analysis. The result can be not accurate because histogram analysis analyzed the whole image. Therefore, if the analysis area is not specified, the result will be not accurate and efficient. The retina movement shows the fatigue level of the driver. For example, if the driver’s eyes are closed about more than 5 seconds in the last 60 seconds, the driver considered as drowsiness. Based on the fact that driver’s eye movement can be used to recognize the level of drowsiness, a sensor can be developing by using image processing analysis in MATLAB. The image processing analysis that will be used is histogram analysis. This system will be developing only on software part

Item Type: Undergraduates Project Papers
Additional Information: Project paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2010, SV: Dr. Kamarul Hawari Ghazali
Uncontrolled Keywords: Image processing, Drowsiness; Physiological aspects; Human face recognition (Computer science)
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Syed Mohd Faiz
Date Deposited: 06 Jan 2012 03:02
Last Modified: 06 Apr 2017 07:56
URI: http://umpir.ump.edu.my/id/eprint/1978
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