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Evaluation of facial detection using adaboost and morphology / Maisarah Aripin

Face detection is a very important process and become part of face recognition. People are slightly aware of its significant and sometimes camiot really determine a face in an image before recognize it. This situation usually happened to the beginner. In recent years, there are a lot of researche...

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Main Author: Aripin, Maisarah
Format: Thesis
Language:English
Published: Faculty of Computer and Mathematical Sciences 2007
Subjects:
Electronic Computers. Computer Science
Online Access:http://ir.uitm.edu.my/id/eprint/1539/1/TD_MAISARAH%20ARIPIN%20CS%2007_5%20P01.pdf
http://ir.uitm.edu.my/id/eprint/1539/
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spelling my.uitm.ir.15392019-11-14T03:12:45Z http://ir.uitm.edu.my/id/eprint/1539/ Evaluation of facial detection using adaboost and morphology / Maisarah Aripin Aripin, Maisarah Electronic Computers. Computer Science Face detection is a very important process and become part of face recognition. People are slightly aware of its significant and sometimes camiot really determine a face in an image before recognize it. This situation usually happened to the beginner. In recent years, there are a lot of researches on face detection method. Thus, a lot of techniques have been discovered in order to get a better technique and improvement in this area of study. Each of those techniques has its own effectiveness in face detection, For example knowledge based method that able to work well for face localization in uncluttered background. Beside that, there is also another method that has the capability to run in real time such as Adaboost. However, this research is only focusing on two techniques, which are Adaboost and Morphology. Both of these algorithms are capable in face detection but serve up in different way. Thus, the objective of this research is to evaluate face detection tool using Adaboost and Morphology and to find out the effectiveness of both algorithms. The system that has been used to test the images is Kihwan's Face Detector. Analysis shows that this system is good in detecting large size images using Adaboost After sizes of the images have been standardizing to become 400 x 300 pixels, it shows that this system can performs better by using Morphology as the technique. Faculty of Computer and Mathematical Sciences 2007 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/1539/1/TD_MAISARAH%20ARIPIN%20CS%2007_5%20P01.pdf Aripin, Maisarah (2007) Evaluation of facial detection using adaboost and morphology / Maisarah Aripin. Degree thesis, Universiti Teknologi MARA.
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Electronic Computers. Computer Science
spellingShingle Electronic Computers. Computer Science
Aripin, Maisarah
Evaluation of facial detection using adaboost and morphology / Maisarah Aripin
description Face detection is a very important process and become part of face recognition. People are slightly aware of its significant and sometimes camiot really determine a face in an image before recognize it. This situation usually happened to the beginner. In recent years, there are a lot of researches on face detection method. Thus, a lot of techniques have been discovered in order to get a better technique and improvement in this area of study. Each of those techniques has its own effectiveness in face detection, For example knowledge based method that able to work well for face localization in uncluttered background. Beside that, there is also another method that has the capability to run in real time such as Adaboost. However, this research is only focusing on two techniques, which are Adaboost and Morphology. Both of these algorithms are capable in face detection but serve up in different way. Thus, the objective of this research is to evaluate face detection tool using Adaboost and Morphology and to find out the effectiveness of both algorithms. The system that has been used to test the images is Kihwan's Face Detector. Analysis shows that this system is good in detecting large size images using Adaboost After sizes of the images have been standardizing to become 400 x 300 pixels, it shows that this system can performs better by using Morphology as the technique.
format Thesis
author Aripin, Maisarah
author_facet Aripin, Maisarah
author_sort Aripin, Maisarah
title Evaluation of facial detection using adaboost and morphology / Maisarah Aripin
title_short Evaluation of facial detection using adaboost and morphology / Maisarah Aripin
title_full Evaluation of facial detection using adaboost and morphology / Maisarah Aripin
title_fullStr Evaluation of facial detection using adaboost and morphology / Maisarah Aripin
title_full_unstemmed Evaluation of facial detection using adaboost and morphology / Maisarah Aripin
title_sort evaluation of facial detection using adaboost and morphology / maisarah aripin
publisher Faculty of Computer and Mathematical Sciences
publishDate 2007
url http://ir.uitm.edu.my/id/eprint/1539/1/TD_MAISARAH%20ARIPIN%20CS%2007_5%20P01.pdf
http://ir.uitm.edu.my/id/eprint/1539/
_version_ 1685648155153006592
score 13.211869

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