Face Recognition in Uncontrolled Indoor Environment

A Master of Science thesis in Electrical Engineering by Kamal Adel Abuqaaud entitled, "Face Recognition in Uncontrolled Indoor Environment," submitted in June 2013. Thesis advisor is Dr. Khaled Assaleh and Co-advisor is Dr. Tamer Shanableh. Available are both soft and hard copies of the th...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Abuqaaud, Kamal Adel (author)
التنسيق: doctoralThesis
منشور في: 2013
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/11073/5911
الوسوم: إضافة وسم
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author Abuqaaud, Kamal Adel
author_facet Abuqaaud, Kamal Adel
author_role author
dc.contributor.none.fl_str_mv Assaleh, Khaled
Shanableh, Tamer
dc.creator.none.fl_str_mv Abuqaaud, Kamal Adel
dc.date.none.fl_str_mv 2013-09-18T08:31:02Z
2013-09-18T08:31:02Z
2013-06
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 35.232-2013.38
http://hdl.handle.net/11073/5911
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv face recognition
spatial differential operators (SDO)
Eigenfaces
discrete cosine transform (DCT)
grey level co-occurence matrix (GLCM)
principle component analysis (PCA)
linear discriminant function (LDF)
Human face recognition (Computer science)
Biometric identification
dc.title.none.fl_str_mv Face Recognition in Uncontrolled Indoor Environment
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Electrical Engineering by Kamal Adel Abuqaaud entitled, "Face Recognition in Uncontrolled Indoor Environment," submitted in June 2013. Thesis advisor is Dr. Khaled Assaleh and Co-advisor is Dr. Tamer Shanableh. Available are both soft and hard copies of the thesis.
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network_acronym_str aus
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oai_identifier_str oai:repository.aus.edu:11073/5911
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repository.mail.fl_str_mv
repository.name.fl_str_mv
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spelling Face Recognition in Uncontrolled Indoor EnvironmentAbuqaaud, Kamal Adelface recognitionspatial differential operators (SDO)Eigenfacesdiscrete cosine transform (DCT)grey level co-occurence matrix (GLCM)principle component analysis (PCA)linear discriminant function (LDF)Human face recognition (Computer science)Biometric identificationA Master of Science thesis in Electrical Engineering by Kamal Adel Abuqaaud entitled, "Face Recognition in Uncontrolled Indoor Environment," submitted in June 2013. Thesis advisor is Dr. Khaled Assaleh and Co-advisor is Dr. Tamer Shanableh. Available are both soft and hard copies of the thesis.Face recognition (FR) is one of the most convenient biometric systems even though it is not currently the most reliable one. Especially when images for (FR) system are captured by surveillance cameras, such cameras often produce low quality images which make recognition more difficult and less reliable. This study uses a recently published database called "SCface database" which emphasizes the challenges of face recognition in uncontrolled indoor conditions such as lighting conditions, face pose, facial expression and distance to camera. More specifically, the recognition is done using different cameras of different resolutions and imaging sensors. The aim of this study is to examine the effect of camera quality and distance from the camera with regards to face recognition rates by analyzing different face recognition schemes such as Eigenfaces, Discrete Cosine Transform (DCT), Wavelet Transform, Gray Level Concurrence Matrix (GLCM) and Spatial Differential Operators (SDO). Principal Component Analysis (PCA), Zonal coding and spectral regression were also investigated as various dimensionality reduction approaches. At the classification stage a variety types of classifiers were tested and compared such as: Linear Discriminant Function (LDF), KNN classifier, polynomial classifiers and Neural Networks. As a result we developed a reliable face recognition system that recognizes faces captured by different cameras in terms of quality and resolution at different distances in surveillance conditions. In our proposed algorithm, face images are preprocessed by means of; skin segmentation, color transformation, cropping, normalization and filtering. Then both Spatial Differential Operators (SDO) and Discrete Cosine Transform (DCT) are applied to extract features, and Principal Component Analysis (PCA) is employed to reduce dimensionality. Linear Discriminant Function (LDF) is utilized as a classifier. The proposed system is compared with the well-known eigenfaces recognition solution. Experimental results show that the proposed system yields superior recognition rates compared to those obtained by the recently published solutions.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE)Assaleh, KhaledShanableh, Tamer2013-09-18T08:31:02Z2013-09-18T08:31:02Z2013-06info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2013.38http://hdl.handle.net/11073/5911en_USoai:repository.aus.edu:11073/59112025-06-26T12:23:53Z
spellingShingle Face Recognition in Uncontrolled Indoor Environment
Abuqaaud, Kamal Adel
face recognition
spatial differential operators (SDO)
Eigenfaces
discrete cosine transform (DCT)
grey level co-occurence matrix (GLCM)
principle component analysis (PCA)
linear discriminant function (LDF)
Human face recognition (Computer science)
Biometric identification
status_str publishedVersion
title Face Recognition in Uncontrolled Indoor Environment
title_full Face Recognition in Uncontrolled Indoor Environment
title_fullStr Face Recognition in Uncontrolled Indoor Environment
title_full_unstemmed Face Recognition in Uncontrolled Indoor Environment
title_short Face Recognition in Uncontrolled Indoor Environment
title_sort Face Recognition in Uncontrolled Indoor Environment
topic face recognition
spatial differential operators (SDO)
Eigenfaces
discrete cosine transform (DCT)
grey level co-occurence matrix (GLCM)
principle component analysis (PCA)
linear discriminant function (LDF)
Human face recognition (Computer science)
Biometric identification
url http://hdl.handle.net/11073/5911