Length estimators for two dimensional and three dimensional images using relative direction chain code

The normal practice of representing an image is in digitized form. Although digitization provides no knowledge about the continuous shape but by the assistance of discrete geometric estimators such as length estimators, it is possible to obtain the feature size. In digitization, two widely used chai...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Dianat, Oldooz
التنسيق: أطروحة
اللغة:English
منشور في: 2010
الموضوعات:
الوصول للمادة أونلاين:http://eprints.utm.my/id/eprint/11503/1/OldoozDianatMFSKSM2010.pdf
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spelling my-utm-ep.115032018-05-30T04:27:13Z Length estimators for two dimensional and three dimensional images using relative direction chain code 2010-02 Dianat, Oldooz QA75 Electronic computers. Computer science The normal practice of representing an image is in digitized form. Although digitization provides no knowledge about the continuous shape but by the assistance of discrete geometric estimators such as length estimators, it is possible to obtain the feature size. In digitization, two widely used chain code schemes for shape representation are Freeman and Bribiesca chain code. The Freeman chain code (FCC) is based on absolute direction while Bribiesca chain code is based on relative direction which makes it stable in shifting, turning, and mirroring movement of image. The main purpose of this study is to implement the relative direction chain code or so-called Bribiesca chain code in length estimator algorithms. This study can be divided into two main parts. The first part is to develop two-dimensional (2D) local and global length estimator based on Bribiesca vertex chain code (VCC). For local length estimator, all regular grids namely rectangular, hexagonal and triangular are applied. For global length estimator, only rectangular grid is considered. The second part is to develop threedimensional (3D) local length estimator based on Bribiesca Orthogonal Directional Change Chain Code (ODCCC). The process is divided into quantization of curve, chain code extraction, and development of length estimators. In quantization, different methods are implemented such as Grid Intersection Quantization, Grid Intersection- Enneagon Quantization, and Cube Quantization. There are four equations and one algorithm proposed for length estimation. The results of the proposed methods are promising such that the length estimators for 2D and 3D images become independent from starting point, and also the 2D global length estimator covers offline and online algorithm. Finally the comparison between the proposed and the established length estimators by FCC gives similar performance, however the resultant visualization of proposed algorithm works better. 2010-02 Thesis http://eprints.utm.my/id/eprint/11503/ http://eprints.utm.my/id/eprint/11503/1/OldoozDianatMFSKSM2010.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computer Science and Information Systems Faculty of Computer Science and Information System
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
language English
topic QA75 Electronic computers
Computer science
spellingShingle QA75 Electronic computers
Computer science
Dianat, Oldooz
Length estimators for two dimensional and three dimensional images using relative direction chain code
description The normal practice of representing an image is in digitized form. Although digitization provides no knowledge about the continuous shape but by the assistance of discrete geometric estimators such as length estimators, it is possible to obtain the feature size. In digitization, two widely used chain code schemes for shape representation are Freeman and Bribiesca chain code. The Freeman chain code (FCC) is based on absolute direction while Bribiesca chain code is based on relative direction which makes it stable in shifting, turning, and mirroring movement of image. The main purpose of this study is to implement the relative direction chain code or so-called Bribiesca chain code in length estimator algorithms. This study can be divided into two main parts. The first part is to develop two-dimensional (2D) local and global length estimator based on Bribiesca vertex chain code (VCC). For local length estimator, all regular grids namely rectangular, hexagonal and triangular are applied. For global length estimator, only rectangular grid is considered. The second part is to develop threedimensional (3D) local length estimator based on Bribiesca Orthogonal Directional Change Chain Code (ODCCC). The process is divided into quantization of curve, chain code extraction, and development of length estimators. In quantization, different methods are implemented such as Grid Intersection Quantization, Grid Intersection- Enneagon Quantization, and Cube Quantization. There are four equations and one algorithm proposed for length estimation. The results of the proposed methods are promising such that the length estimators for 2D and 3D images become independent from starting point, and also the 2D global length estimator covers offline and online algorithm. Finally the comparison between the proposed and the established length estimators by FCC gives similar performance, however the resultant visualization of proposed algorithm works better.
format Thesis
qualification_level Master's degree
author Dianat, Oldooz
author_facet Dianat, Oldooz
author_sort Dianat, Oldooz
title Length estimators for two dimensional and three dimensional images using relative direction chain code
title_short Length estimators for two dimensional and three dimensional images using relative direction chain code
title_full Length estimators for two dimensional and three dimensional images using relative direction chain code
title_fullStr Length estimators for two dimensional and three dimensional images using relative direction chain code
title_full_unstemmed Length estimators for two dimensional and three dimensional images using relative direction chain code
title_sort length estimators for two dimensional and three dimensional images using relative direction chain code
granting_institution Universiti Teknologi Malaysia, Faculty of Computer Science and Information Systems
granting_department Faculty of Computer Science and Information System
publishDate 2010
url http://eprints.utm.my/id/eprint/11503/1/OldoozDianatMFSKSM2010.pdf
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