Face recognition using eigeneyes / Nor Amelia Abiden

As continuous research is being conducted in the area of computer vision, one of the most practical applications under vigorous development is the face recognition system. Face Recognition is an emerging field of research with many challenges such as large set of images and improper illuminating con...

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Main Author:	Abiden, Nor Amelia
Format:	Thesis
Language:	English
Published:	2007
Subjects:	Mathematical physics
Online Access:	https://ir.uitm.edu.my/id/eprint/102945/1/102945.pdf
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spelling	my-uitm-ir.1029452024-11-21T06:30:27Z Face recognition using eigeneyes / Nor Amelia Abiden 2007 Abiden, Nor Amelia Mathematical physics As continuous research is being conducted in the area of computer vision, one of the most practical applications under vigorous development is the face recognition system. Face Recognition is an emerging field of research with many challenges such as large set of images and improper illuminating conditions. Eigeneye approach is considered to overcome these obstacles in developing a system for Face Recognition. There are various techniques used for processing the image in order to handle bad illumination and face alignment problem. In this project, the Eigeneye approach is used for face recognition. This project is conducted to compare an unknown eye structure to a known subject's eye and face recognition is achieved if the unknown eyes match with that of known trained eyes. The face recognition utilizes cropped images are to render a two-dimensional representation of a human eye area. The system then projects the image onto an 'eye space' that best encodes the variation among known eye images. The eye space is defined as the 'eigeneyes', which are eigenvectors of the set of eyes. The framework provides the ability to learn to recognize new faces in an unsupervised manner. Eigeneyes are eigenvectors of covariance matrix, representing given eye image space. In this project, a large set of eye images from a group of known faces are trained, and an unknown eye images are used for testing. Euclidean Distance is used to compute minimum distance and this will determine whether the input eye image match with the eye images in the training set. This technique of face recognition is able to recognize whether the test eye images are human faces. When the maximum value is around 6+e003 and the minimum value is more than 4+e003. 2007 Thesis https://ir.uitm.edu.my/id/eprint/102945/ https://ir.uitm.edu.my/id/eprint/102945/1/102945.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Abd Jalil, Nor'Aini
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Abd Jalil, Nor'Aini
topic	Mathematical physics
spellingShingle	Mathematical physics Abiden, Nor Amelia Face recognition using eigeneyes / Nor Amelia Abiden
description	As continuous research is being conducted in the area of computer vision, one of the most practical applications under vigorous development is the face recognition system. Face Recognition is an emerging field of research with many challenges such as large set of images and improper illuminating conditions. Eigeneye approach is considered to overcome these obstacles in developing a system for Face Recognition. There are various techniques used for processing the image in order to handle bad illumination and face alignment problem. In this project, the Eigeneye approach is used for face recognition. This project is conducted to compare an unknown eye structure to a known subject's eye and face recognition is achieved if the unknown eyes match with that of known trained eyes. The face recognition utilizes cropped images are to render a two-dimensional representation of a human eye area. The system then projects the image onto an 'eye space' that best encodes the variation among known eye images. The eye space is defined as the 'eigeneyes', which are eigenvectors of the set of eyes. The framework provides the ability to learn to recognize new faces in an unsupervised manner. Eigeneyes are eigenvectors of covariance matrix, representing given eye image space. In this project, a large set of eye images from a group of known faces are trained, and an unknown eye images are used for testing. Euclidean Distance is used to compute minimum distance and this will determine whether the input eye image match with the eye images in the training set. This technique of face recognition is able to recognize whether the test eye images are human faces. When the maximum value is around 6+e003 and the minimum value is more than 4+e003.
format	Thesis
qualification_level	Bachelor degree
author	Abiden, Nor Amelia
author_facet	Abiden, Nor Amelia
author_sort	Abiden, Nor Amelia
title	Face recognition using eigeneyes / Nor Amelia Abiden
title_short	Face recognition using eigeneyes / Nor Amelia Abiden
title_full	Face recognition using eigeneyes / Nor Amelia Abiden
title_fullStr	Face recognition using eigeneyes / Nor Amelia Abiden
title_full_unstemmed	Face recognition using eigeneyes / Nor Amelia Abiden
title_sort	face recognition using eigeneyes / nor amelia abiden
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Electrical Engineering
publishDate	2007
url	https://ir.uitm.edu.my/id/eprint/102945/1/102945.pdf
_version_	1818588064992198656

Face recognition using eigeneyes / Nor Amelia Abiden

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