Staff View: Eye closure and open detection using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected components utilisation

Eye closure and open detection using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected components utilisation

Eye closure detection is an important operation prior to carry out the main algorithm such as iris recognition algorithms, and eye tracking algorithms. This paper introduces a method to detect eye closure using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected component util...

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Main Authors:	Mat Ibrahim, Masrullizam, Awang Md Isa, Azmi, Darsono, Abd Majid
Format:	Conference or Workshop Item
Language:	English
Published:	2014
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://eprints.utem.edu.my/id/eprint/14024/1/Eye_Closure_and_Open_Detection_Using_Adaptive_Thresholding_Histogram_Enhancement_%28ATHE%29.pdf http://eprints.utem.edu.my/id/eprint/14024/
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id	my.utem.eprints.14024
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spelling	my.utem.eprints.140242023-05-30T12:25:00Z http://eprints.utem.edu.my/id/eprint/14024/ Eye closure and open detection using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected components utilisation Mat Ibrahim, Masrullizam Awang Md Isa, Azmi Darsono, Abd Majid QA75 Electronic computers. Computer science Eye closure detection is an important operation prior to carry out the main algorithm such as iris recognition algorithms, and eye tracking algorithms. This paper introduces a method to detect eye closure using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected component utilisation. The ATHE technique is a combination of histogram enhancement and estimation threshold technique. Firstly, in this proposed method the eye region is required to be localised. The ATHE technique enhances the eye region image then and yield the threshold value to segment the iris region. Based on the segmentation result, the connected components of binary image are used to classify the state of eye whether open or close. This classification is based on the shape and size of segmented region. The performance of the proposed technique is tested and validated by using UBIRIS, MMU and CASIA iris image database. 2014 Conference or Workshop Item PeerReviewed text en http://eprints.utem.edu.my/id/eprint/14024/1/Eye_Closure_and_Open_Detection_Using_Adaptive_Thresholding_Histogram_Enhancement_%28ATHE%29.pdf Mat Ibrahim, Masrullizam and Awang Md Isa, Azmi and Darsono, Abd Majid (2014) Eye closure and open detection using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected components utilisation. In: Intelligent and Advanced Systems (ICIAS), 2014 5th International Conference, 3-5 June 2014 , KLCC Kuala Lumpur.
institution	Universiti Teknikal Malaysia Melaka
building	UTEM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknikal Malaysia Melaka
content_source	UTEM Institutional Repository
url_provider	http://eprints.utem.edu.my/
language	English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Mat Ibrahim, Masrullizam Awang Md Isa, Azmi Darsono, Abd Majid Eye closure and open detection using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected components utilisation
description	Eye closure detection is an important operation prior to carry out the main algorithm such as iris recognition algorithms, and eye tracking algorithms. This paper introduces a method to detect eye closure using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected component utilisation. The ATHE technique is a combination of histogram enhancement and estimation threshold technique. Firstly, in this proposed method the eye region is required to be localised. The ATHE technique enhances the eye region image then and yield the threshold value to segment the iris region. Based on the segmentation result, the connected components of binary image are used to classify the state of eye whether open or close. This classification is based on the shape and size of segmented region. The performance of the proposed technique is tested and validated by using UBIRIS, MMU and CASIA iris image database.
format	Conference or Workshop Item
author	Mat Ibrahim, Masrullizam Awang Md Isa, Azmi Darsono, Abd Majid
author_facet	Mat Ibrahim, Masrullizam Awang Md Isa, Azmi Darsono, Abd Majid
author_sort	Mat Ibrahim, Masrullizam
title	Eye closure and open detection using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected components utilisation
title_short	Eye closure and open detection using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected components utilisation
title_full	Eye closure and open detection using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected components utilisation
title_fullStr	Eye closure and open detection using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected components utilisation
title_full_unstemmed	Eye closure and open detection using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected components utilisation
title_sort	eye closure and open detection using adaptive thresholding histogram enhancement (athe) technique and connected components utilisation
publishDate	2014
url	http://eprints.utem.edu.my/id/eprint/14024/1/Eye_Closure_and_Open_Detection_Using_Adaptive_Thresholding_Histogram_Enhancement_%28ATHE%29.pdf http://eprints.utem.edu.my/id/eprint/14024/
_version_	1768012346000670720
score	13.211869

Eye closure and open detection using Adaptive Thresholding Histogram Enhancement (ATHE) technique and connected components utilisation

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