G² parametric curve and surface fitting using beta-spline / Normi Abdul Hadi

Advancement of the imaging technology nowadays demands sophisticated method to represent the captured image in the form of curves and surfaces. However, the challenge in curve and surface fitting techniques is the smoothness and accurateness of the result and the complexity of the techniques. Theref...

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Main Author:	Abdul Hadi, Normi
Format:	Thesis
Language:	English
Published:	2015
Online Access:	http://ir.uitm.edu.my/id/eprint/17790/ http://ir.uitm.edu.my/id/eprint/17790/2/TP_NORMI%20ABDUL%20HADI%20CS%2015_5.pdf

id	uitm-17790
recordtype	eprints
spelling	uitm-177902018-09-27T02:22:50Z http://ir.uitm.edu.my/id/eprint/17790/ G² parametric curve and surface fitting using beta-spline / Normi Abdul Hadi Abdul Hadi, Normi Advancement of the imaging technology nowadays demands sophisticated method to represent the captured image in the form of curves and surfaces. However, the challenge in curve and surface fitting techniques is the smoothness and accurateness of the result and the complexity of the techniques. Therefore, the primary goal of this research is to develop new curve and surface fitting techniques using beta-spline which has G2 continuity, high accuracy and less number of computations. This is due to the properties of cubic beta-spline itself with G2 conditions, and located close to the control polygon. Additionally, beta-spline can be controlled in three ways using control points, shape parameters and weights. In beta-spline curve fitting, the control points are calculated using least squares method. The data points are first segmented in comer detection process, then the curve control points are calculated based on the comer points. The developed curve fitting technique is applied on 2D font of ‘<_s’ (ya) and‘Є’ (epsilon). The results are then compared with the another technique using Bspline in terms of total processing time, approximation error, and the number of computation in the algorithm. For beta-spline surface fitting, a new technique to solve branching contours has been carried out. An intermediate contour called composite contour is generated and inserted between the two adjacent image slices. Beta-spline surface is then fitted to the extracted data points from each slice. The developed surface fitting algorithm is applied on 3D Computerized Tomography (CT) image of human face and Stanford bunny. The reconstructed 3D images are compared visually with the images using the other techniques. The results show that the reconstructed images using beta-spline surface give similar result obtained using the other techniques. 2015 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/17790/2/TP_NORMI%20ABDUL%20HADI%20CS%2015_5.pdf Abdul Hadi, Normi (2015) G² parametric curve and surface fitting using beta-spline / Normi Abdul Hadi. PhD thesis, Universiti Teknologi MARA.
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
description	Advancement of the imaging technology nowadays demands sophisticated method to represent the captured image in the form of curves and surfaces. However, the challenge in curve and surface fitting techniques is the smoothness and accurateness of the result and the complexity of the techniques. Therefore, the primary goal of this research is to develop new curve and surface fitting techniques using beta-spline which has G2 continuity, high accuracy and less number of computations. This is due to the properties of cubic beta-spline itself with G2 conditions, and located close to the control polygon. Additionally, beta-spline can be controlled in three ways using control points, shape parameters and weights. In beta-spline curve fitting, the control points are calculated using least squares method. The data points are first segmented in comer detection process, then the curve control points are calculated based on the comer points. The developed curve fitting technique is applied on 2D font of ‘<_s’ (ya) and‘Є’ (epsilon). The results are then compared with the another technique using Bspline in terms of total processing time, approximation error, and the number of computation in the algorithm. For beta-spline surface fitting, a new technique to solve branching contours has been carried out. An intermediate contour called composite contour is generated and inserted between the two adjacent image slices. Beta-spline surface is then fitted to the extracted data points from each slice. The developed surface fitting algorithm is applied on 3D Computerized Tomography (CT) image of human face and Stanford bunny. The reconstructed 3D images are compared visually with the images using the other techniques. The results show that the reconstructed images using beta-spline surface give similar result obtained using the other techniques.
format	Thesis
author	Abdul Hadi, Normi
spellingShingle	Abdul Hadi, Normi G² parametric curve and surface fitting using beta-spline / Normi Abdul Hadi
author_facet	Abdul Hadi, Normi
author_sort	Abdul Hadi, Normi
title	G² parametric curve and surface fitting using beta-spline / Normi Abdul Hadi
title_short	G² parametric curve and surface fitting using beta-spline / Normi Abdul Hadi
title_full	G² parametric curve and surface fitting using beta-spline / Normi Abdul Hadi
title_fullStr	G² parametric curve and surface fitting using beta-spline / Normi Abdul Hadi
title_full_unstemmed	G² parametric curve and surface fitting using beta-spline / Normi Abdul Hadi
title_sort	g² parametric curve and surface fitting using beta-spline / normi abdul hadi
publishDate	2015
url	http://ir.uitm.edu.my/id/eprint/17790/ http://ir.uitm.edu.my/id/eprint/17790/2/TP_NORMI%20ABDUL%20HADI%20CS%2015_5.pdf
first_indexed	2023-09-18T22:59:04Z
last_indexed	2023-09-18T22:59:04Z
_version_	1777418051000467456

G² parametric curve and surface fitting using beta-spline / Normi Abdul Hadi

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