Hand recognition method based on Eigen-hand (principal component analysis) technique
Other Title(s)
طريقة اليد المستندة على تقنية تحليل المركبات الأساسية للأيدي الذاتية
Dissertant
Thesis advisor
Comitee Members
al-Zuki, Ali Abd D.
Dakhil, Zahidah Ahmad
Ghazal, Nawal Khalaf
University
University of Baghdad
Faculty
College of Science
Department
Department of Physics
University Country
Iraq
Degree
Master
Degree Date
2011
English Abstract
In this thesis, the Principal Component Analysis (PCA) based method (namely Eigenhand), is used to verify persons from their hand’s image.
Our approach treats the hand recognition and verification problems as an essentially 2D-problem rather than requiring recovery of 3D geometry, taking advantage of the fact that hand’s images can be described by a small set of 2D characteristics features.
The extracted features for the recognition process have been referred to as “Eigen hands” because they represent the eigenvectors of the set of the trained and tested hands.
The verification operation between the trained hand’s images (i.e.
preserved in the Database) and the input “unknown” hand image is performed by utilizing the Minimum-Mean- Distance “MMD” criterion.
The designed system output is either "Verified" or "Unverified".
Several amounts of different noises (e.g.
Gaussian, Salt-and-pepper, Uniform) have been added to the tested hand to measure the reliability of our presented verification system.
Additionally, the effects of image rotation have, also, been studied by rotating the test image few degrees (in clock and anti-clock directions).
Moreover, the scaling effects have also be checked by enlarging the test image several percentage amount, and shifting (directionality left and right) have also been carried out
Main Subjects
No. of Pages
90
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : General introduction.
Chapter Two : Pattern recognition methodologies.
Chapter Three : The PCA eigenhand recognition method.
Chapter Four : The experimental test and results.
Chapter Five : Conclusions and suggestions for work.
References.
American Psychological Association (APA)
Hamid, Husayn Abd Allah. (2011). Hand recognition method based on Eigen-hand (principal component analysis) technique. (Master's theses Theses and Dissertations Master). University of Baghdad, Iraq
https://search.emarefa.net/detail/BIM-606337
Modern Language Association (MLA)
Hamid, Husayn Abd Allah. Hand recognition method based on Eigen-hand (principal component analysis) technique. (Master's theses Theses and Dissertations Master). University of Baghdad. (2011).
https://search.emarefa.net/detail/BIM-606337
American Medical Association (AMA)
Hamid, Husayn Abd Allah. (2011). Hand recognition method based on Eigen-hand (principal component analysis) technique. (Master's theses Theses and Dissertations Master). University of Baghdad, Iraq
https://search.emarefa.net/detail/BIM-606337
Language
English
Data Type
Arab Theses
Record ID
BIM-606337