Facial recognition using empirical mode decomposition, Multi-linear principal component analysis and post-processing using expectation maximization algorithm

Cataloged from PDF version of thesis report.

Opis bibliograficzny
1. autor: Chowdhury, Mabrur Mujib
Kolejni autorzy: Alom, Md. Zahangir
Format: Praca dyplomowa
Język:English
Wydane: BRAC University 2014
Hasła przedmiotowe:
Dostęp online:http://hdl.handle.net/10361/3572
id 10361-3572
record_format dspace
spelling 10361-35722022-01-26T10:04:49Z Facial recognition using empirical mode decomposition, Multi-linear principal component analysis and post-processing using expectation maximization algorithm Chowdhury, Mabrur Mujib Alom, Md. Zahangir Department of Computer Science and Engineering, BRAC University Computer science and engineering Facial recognition Cataloged from PDF version of thesis report. Includes bibliographical references (page 49 - 50). This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2014. The field of facial recognition is rapidly growing into a vital part of our everyday lives. The use of facial recognition systems has been extended primarily from security purposes to social networking sites, managing fraud, and improved user experience. Numerous algorithms have been designed to perform facial recognition with greatest accuracy. The use of several preprocessing and post-processing techniques is also known to improve the effectiveness of these recognition algorithms. This paper focuses on a three-tier approach towards facial recognition. A widely popular recognition algorithm used today is the Principal Component Analysis (PCA). Throughout the years, there have been many improvements and extensions to the original PCA. One such extension is the Multi-linear PCA, which is the algorithm I have used in my study. Studies have shown that results of the recognition algorithm can be greatly improved by applying preprocessing techniques to the images before feeding them into the main recognition algorithm. Therefore, in addition to the Multi-linear PCA, I will be using Empirical Mode Decomposition (EMD) for preprocessing. Furthermore, I plan to run an Expectation Maximization (EM) algorithm which estimates Maximum Likelihood values for information which may be missing from the dataset. Applying these three strategies simultaneously would allow us to have a more efficient, secure and robust facial recognition system. Mabrur Mujib Chowdhury B. Computer Science and Engineering 2014-09-09T09:48:35Z 2014-09-09T09:48:35Z 2014 9/1/2014 Thesis ID 14341004 http://hdl.handle.net/10361/3572 en BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 51 pages application/pdf BRAC University
institution Brac University
collection Institutional Repository
language English
topic Computer science and engineering
Facial recognition
spellingShingle Computer science and engineering
Facial recognition
Chowdhury, Mabrur Mujib
Facial recognition using empirical mode decomposition, Multi-linear principal component analysis and post-processing using expectation maximization algorithm
description Cataloged from PDF version of thesis report.
author2 Alom, Md. Zahangir
author_facet Alom, Md. Zahangir
Chowdhury, Mabrur Mujib
format Thesis
author Chowdhury, Mabrur Mujib
author_sort Chowdhury, Mabrur Mujib
title Facial recognition using empirical mode decomposition, Multi-linear principal component analysis and post-processing using expectation maximization algorithm
title_short Facial recognition using empirical mode decomposition, Multi-linear principal component analysis and post-processing using expectation maximization algorithm
title_full Facial recognition using empirical mode decomposition, Multi-linear principal component analysis and post-processing using expectation maximization algorithm
title_fullStr Facial recognition using empirical mode decomposition, Multi-linear principal component analysis and post-processing using expectation maximization algorithm
title_full_unstemmed Facial recognition using empirical mode decomposition, Multi-linear principal component analysis and post-processing using expectation maximization algorithm
title_sort facial recognition using empirical mode decomposition, multi-linear principal component analysis and post-processing using expectation maximization algorithm
publisher BRAC University
publishDate 2014
url http://hdl.handle.net/10361/3572
work_keys_str_mv AT chowdhurymabrurmujib facialrecognitionusingempiricalmodedecompositionmultilinearprincipalcomponentanalysisandpostprocessingusingexpectationmaximizationalgorithm
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