Division-Based Methods For Large Point Sets Registration

Pendaftaran set titik adalah satu langkah penting untuk mengukur persamaan antara dua set titik dan digunakan secara meluas dalam penglihatan komputer, grafik komputer, analisis imej perubatan, dan sebagainya. Peralatan semasa mampu menyediakan data dengan butiran terperinci sebagai set titik bes...

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Main Author:	Chen , Junfen
Format:	Thesis
Language:	English
Published:	2016
Subjects:	QA75.5-76.95 Electronic computers Computer science
Online Access:	http://eprints.usm.my/31827/1/CHEN_JUNFEN_24%28NN%29.pdf
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id	my-usm-ep.31827
record_format	uketd_dc
spelling	my-usm-ep.318272019-04-12T05:25:22Z Division-Based Methods For Large Point Sets Registration 2016-03 Chen , Junfen QA75.5-76.95 Electronic computers. Computer science Pendaftaran set titik adalah satu langkah penting untuk mengukur persamaan antara dua set titik dan digunakan secara meluas dalam penglihatan komputer, grafik komputer, analisis imej perubatan, dan sebagainya. Peralatan semasa mampu menyediakan data dengan butiran terperinci sebagai set titik besar. Walau bagaimanapun, prestasi kaedah pendaftaran konvensional menurun secara mendadak apabila saiz set titik meningkat. Dalam tesis ini, tiga kaedah pendaftaran set titik terkenal dan antara yang mempunyai prestasi terbaik dipertimbangkan untuk mengkaji pengubahan kaedah konvensional kepada kaedah yang menangani pendaftaran set titik besar dengan cekap. Kaedah-kaedah tersebut adalah Lelaran Titik Terdekat (ICP), Peralihan Titik Bersambung (CPD) dan Model Campuran Gaussian berasaskan Plat-nipis Splin. Point sets registration is a key step for measuring the similarity between two point sets and widely used in various fields such as computer vision, computer graphics, medical image analysis, to name a few. The current devices can capture data with great details as large point set. However, conventional registration methods slow down dramatically as the size of the point set increased. In this thesis, three well-known and among-best-performance point sets registration methods incorporating division schemes are considered to study transforming conventional methods to efficiently deal with large point sets registration. These methods are Iterative Closest Point (ICP), Coherent Point Drift (CPD), and Gaussian mixture models based on thin-plate splines (GMM-TPS). 2016-03 Thesis http://eprints.usm.my/31827/ http://eprints.usm.my/31827/1/CHEN_JUNFEN_24%28NN%29.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Komputer (School of Computer Sciences)
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	QA75.5-76.95 Electronic computers Computer science
spellingShingle	QA75.5-76.95 Electronic computers Computer science Chen , Junfen Division-Based Methods For Large Point Sets Registration
description	Pendaftaran set titik adalah satu langkah penting untuk mengukur persamaan antara dua set titik dan digunakan secara meluas dalam penglihatan komputer, grafik komputer, analisis imej perubatan, dan sebagainya. Peralatan semasa mampu menyediakan data dengan butiran terperinci sebagai set titik besar. Walau bagaimanapun, prestasi kaedah pendaftaran konvensional menurun secara mendadak apabila saiz set titik meningkat. Dalam tesis ini, tiga kaedah pendaftaran set titik terkenal dan antara yang mempunyai prestasi terbaik dipertimbangkan untuk mengkaji pengubahan kaedah konvensional kepada kaedah yang menangani pendaftaran set titik besar dengan cekap. Kaedah-kaedah tersebut adalah Lelaran Titik Terdekat (ICP), Peralihan Titik Bersambung (CPD) dan Model Campuran Gaussian berasaskan Plat-nipis Splin. Point sets registration is a key step for measuring the similarity between two point sets and widely used in various fields such as computer vision, computer graphics, medical image analysis, to name a few. The current devices can capture data with great details as large point set. However, conventional registration methods slow down dramatically as the size of the point set increased. In this thesis, three well-known and among-best-performance point sets registration methods incorporating division schemes are considered to study transforming conventional methods to efficiently deal with large point sets registration. These methods are Iterative Closest Point (ICP), Coherent Point Drift (CPD), and Gaussian mixture models based on thin-plate splines (GMM-TPS).
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Chen , Junfen
author_facet	Chen , Junfen
author_sort	Chen , Junfen
title	Division-Based Methods For Large Point Sets Registration
title_short	Division-Based Methods For Large Point Sets Registration
title_full	Division-Based Methods For Large Point Sets Registration
title_fullStr	Division-Based Methods For Large Point Sets Registration
title_full_unstemmed	Division-Based Methods For Large Point Sets Registration
title_sort	division-based methods for large point sets registration
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Sains Komputer (School of Computer Sciences)
publishDate	2016
url	http://eprints.usm.my/31827/1/CHEN_JUNFEN_24%28NN%29.pdf
_version_	1747820495339782144

Division-Based Methods For Large Point Sets Registration

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