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
Subjects:	Electric apparatus and materials Electric circuits Electric networks Scanning systems
Online Access:	https://ir.uitm.edu.my/id/eprint/15714/1/TP_NORMI%20ABDUL%20HADI%20CS%2015_5.pdf
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id	my-uitm-ir.15714
record_format	uketd_dc
spelling	my-uitm-ir.157142022-03-10T00:15:14Z G2 parametric curve and surface fitting using beta-spline / Normi Abdul Hadi 2015 Abdul Hadi, Normi Electric apparatus and materials. Electric circuits. Electric networks Scanning systems 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‘e’ (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 https://ir.uitm.edu.my/id/eprint/15714/ https://ir.uitm.edu.my/id/eprint/15714/1/TP_NORMI%20ABDUL%20HADI%20CS%2015_5.pdf text en public phd doctoral Universiti Teknologi MARA Faculty of Computer & Mathematical Sciences
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Electric apparatus and materials Electric circuits Electric networks Scanning systems
spellingShingle	Electric apparatus and materials Electric circuits Electric networks Scanning systems Abdul Hadi, Normi G2 parametric curve and surface fitting using beta-spline / Normi Abdul Hadi
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‘e’ (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
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Abdul Hadi, Normi
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
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Computer & Mathematical Sciences
publishDate	2015
url	https://ir.uitm.edu.my/id/eprint/15714/1/TP_NORMI%20ABDUL%20HADI%20CS%2015_5.pdf
_version_	1783733445218795520

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

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