Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin

Image segmentation refers to process of separating out a desire region from an image. Extracting feature in images to get meaningful information is a demanding task as need to extract the information in very large images. However, existing face recognition methods would not perform well under certai...

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Main Author:	Zainal Abidin, Abdul Hakim
Format:	Thesis
Language:	English
Published:	2016
Online Access:	https://ir.uitm.edu.my/id/eprint/18098/1/TD_ABDUL%20HAKIM%20ZAINAL%20ABIDIN%20CS%2016_5.pdf
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id	my-uitm-ir.18098
record_format	uketd_dc
spelling	my-uitm-ir.180982019-02-28T03:46:17Z Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin 2016 Zainal Abidin, Abdul Hakim Image segmentation refers to process of separating out a desire region from an image. Extracting feature in images to get meaningful information is a demanding task as need to extract the information in very large images. However, existing face recognition methods would not perform well under certain conditions. This research purposed clustering algorithm to improve process extracting feature in images to get meaningful information because it can speed up the time to process of extracting meaningful information in images due to the efficient of the algorithm that has high performance to process the image. This research scope are to develop a computer application that can extract meaningful information in images by implement KMeans clustering algorithm 10 self capture facial image will be use as the research subject to test the algorithm that will extracting meaningful information of the person. For this research, the meaningful information that will be extracting is eye feature. Methodology of this research consists of Planning and Analysis, Data Collection, Algorithm Design and Development and Testing. All the process in developing the prototype will be reveal later in this report. The result of this research show that nearly all image has accuracy more than 80% that prove that K-Means clustering algorithm are suitable as method for extracting meaningful information in images. 2016 Thesis https://ir.uitm.edu.my/id/eprint/18098/ https://ir.uitm.edu.my/id/eprint/18098/1/TD_ABDUL%20HAKIM%20ZAINAL%20ABIDIN%20CS%2016_5.pdf text en public dphil degree Universiti Teknologi MARA Faculty of Computer and Mathematical Sciences
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
description	Image segmentation refers to process of separating out a desire region from an image. Extracting feature in images to get meaningful information is a demanding task as need to extract the information in very large images. However, existing face recognition methods would not perform well under certain conditions. This research purposed clustering algorithm to improve process extracting feature in images to get meaningful information because it can speed up the time to process of extracting meaningful information in images due to the efficient of the algorithm that has high performance to process the image. This research scope are to develop a computer application that can extract meaningful information in images by implement KMeans clustering algorithm 10 self capture facial image will be use as the research subject to test the algorithm that will extracting meaningful information of the person. For this research, the meaningful information that will be extracting is eye feature. Methodology of this research consists of Planning and Analysis, Data Collection, Algorithm Design and Development and Testing. All the process in developing the prototype will be reveal later in this report. The result of this research show that nearly all image has accuracy more than 80% that prove that K-Means clustering algorithm are suitable as method for extracting meaningful information in images.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Bachelor degree
author	Zainal Abidin, Abdul Hakim
spellingShingle	Zainal Abidin, Abdul Hakim Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin
author_facet	Zainal Abidin, Abdul Hakim
author_sort	Zainal Abidin, Abdul Hakim
title	Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin
title_short	Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin
title_full	Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin
title_fullStr	Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin
title_full_unstemmed	Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin
title_sort	extracting feature from images by using k-means clustering algorithm / abdul hakim zainal abidin
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2016
url	https://ir.uitm.edu.my/id/eprint/18098/1/TD_ABDUL%20HAKIM%20ZAINAL%20ABIDIN%20CS%2016_5.pdf
_version_	1783733624296701952

Extracting feature from images by using K-Means clustering algorithm / Abdul Hakim Zainal Abidin

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