Hereditary traits based on lips analysis using Ellipse Fitting / Tantty Roshaida Rozaini
Ellipse fitting is the process of finding the edge of the ellipse shape in an image. This process significantly reduces the amount of data in the image, while preserving the most important structural features of that image. Ellipse Fitting is considered to be the ideal edge detection algorithm for i...
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my-uitm-ir.640372023-08-28T04:50:56Z Hereditary traits based on lips analysis using Ellipse Fitting / Tantty Roshaida Rozaini 2010 Rozaini, Tantty Roshaida Ellipse fitting is the process of finding the edge of the ellipse shape in an image. This process significantly reduces the amount of data in the image, while preserving the most important structural features of that image. Ellipse Fitting is considered to be the ideal edge detection algorithm for images that are corrupted with white noise. It consists of several steps that make this method as an optimal edge detector. The objective of this research is gained from understanding of the problem statement. This research intends to get the hereditary ratio of adolescents to parents based on lips features. The main idea of this research is to get the lips features from facial images before proceed to the next process which is comparison technique. In this research, technique selection is done by doing some literature review to find the best one and also studying about the algorithm of each technique has. The result of hereditary ratio will be gained by implementing difference of the distance value. 2010 Thesis https://ir.uitm.edu.my/id/eprint/64037/ https://ir.uitm.edu.my/id/eprint/64037/1/64037.PDF text en public degree Universiti Teknologi Mara (UiTM) Faculty of Computer and Mathematical Sciences Yusoff, Fakhrul Hazman |
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Universiti Teknologi MARA |
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UiTM Institutional Repository |
language |
English |
advisor |
Yusoff, Fakhrul Hazman |
description |
Ellipse fitting is the process of finding the edge of the ellipse shape in an image. This process significantly reduces the amount of data in the image, while preserving the most important structural features of that image. Ellipse Fitting is considered to be the ideal edge detection algorithm for images that are corrupted with white noise. It consists of several steps that make this method as an optimal edge detector. The objective of this research is gained from understanding of the problem statement. This research intends to get the hereditary ratio of adolescents to parents based on lips features. The main idea of this research is to get the lips features from facial images before proceed to the next process which is comparison technique. In this research, technique selection is done by doing some literature review to find the best one and also studying about the algorithm of each technique has. The result of hereditary ratio will be gained by implementing difference of the distance value. |
format |
Thesis |
qualification_level |
Bachelor degree |
author |
Rozaini, Tantty Roshaida |
spellingShingle |
Rozaini, Tantty Roshaida Hereditary traits based on lips analysis using Ellipse Fitting / Tantty Roshaida Rozaini |
author_facet |
Rozaini, Tantty Roshaida |
author_sort |
Rozaini, Tantty Roshaida |
title |
Hereditary traits based on lips analysis using Ellipse Fitting / Tantty Roshaida Rozaini |
title_short |
Hereditary traits based on lips analysis using Ellipse Fitting / Tantty Roshaida Rozaini |
title_full |
Hereditary traits based on lips analysis using Ellipse Fitting / Tantty Roshaida Rozaini |
title_fullStr |
Hereditary traits based on lips analysis using Ellipse Fitting / Tantty Roshaida Rozaini |
title_full_unstemmed |
Hereditary traits based on lips analysis using Ellipse Fitting / Tantty Roshaida Rozaini |
title_sort |
hereditary traits based on lips analysis using ellipse fitting / tantty roshaida rozaini |
granting_institution |
Universiti Teknologi Mara (UiTM) |
granting_department |
Faculty of Computer and Mathematical Sciences |
publishDate |
2010 |
url |
https://ir.uitm.edu.my/id/eprint/64037/1/64037.PDF |
_version_ |
1783735387442642944 |