Automatic image annotation using color segmentation / Siti 'Aisyah Sa'dan

Image can be described as photographed, painted or sculptured. Nowadays, images are extremely shared throughout the Internet. Annotating or captioning can be used to classify images. However, manual annotation is time consuming for large database and there is no standard in caption an image by manua...

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Main Author:	Sa'dan, Siti 'Aisyah
Format:	Thesis
Language:	English
Published:	2009
Online Access:	https://ir.uitm.edu.my/id/eprint/87215/1/87215.pdf
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id	my-uitm-ir.87215
record_format	uketd_dc
spelling	my-uitm-ir.872152024-02-19T01:48:18Z Automatic image annotation using color segmentation / Siti 'Aisyah Sa'dan 2009 Sa'dan, Siti 'Aisyah Image can be described as photographed, painted or sculptured. Nowadays, images are extremely shared throughout the Internet. Annotating or captioning can be used to classify images. However, manual annotation is time consuming for large database and there is no standard in caption an image by manual annotation because it is based on human perception. The objectives of this project are to implement automatic annotation for images using K-means clustering, to develop an automatic image annotation prototype using color segmentation and to test the efficiency of the automatic image annotation prototype. The scope of this project is digital image of beach photographs with JPegs format. This project is implemented using a basic KMeans clustering as the algorithm for color segmentation and using direct technique to annotate the colors with the appropriate words by using predefined colors. 2009 Thesis https://ir.uitm.edu.my/id/eprint/87215/ https://ir.uitm.edu.my/id/eprint/87215/1/87215.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Computer and Mathematical Sciences Jamil, Nursuriati
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Jamil, Nursuriati
description	Image can be described as photographed, painted or sculptured. Nowadays, images are extremely shared throughout the Internet. Annotating or captioning can be used to classify images. However, manual annotation is time consuming for large database and there is no standard in caption an image by manual annotation because it is based on human perception. The objectives of this project are to implement automatic annotation for images using K-means clustering, to develop an automatic image annotation prototype using color segmentation and to test the efficiency of the automatic image annotation prototype. The scope of this project is digital image of beach photographs with JPegs format. This project is implemented using a basic KMeans clustering as the algorithm for color segmentation and using direct technique to annotate the colors with the appropriate words by using predefined colors.
format	Thesis
qualification_level	Bachelor degree
author	Sa'dan, Siti 'Aisyah
spellingShingle	Sa'dan, Siti 'Aisyah Automatic image annotation using color segmentation / Siti 'Aisyah Sa'dan
author_facet	Sa'dan, Siti 'Aisyah
author_sort	Sa'dan, Siti 'Aisyah
title	Automatic image annotation using color segmentation / Siti 'Aisyah Sa'dan
title_short	Automatic image annotation using color segmentation / Siti 'Aisyah Sa'dan
title_full	Automatic image annotation using color segmentation / Siti 'Aisyah Sa'dan
title_fullStr	Automatic image annotation using color segmentation / Siti 'Aisyah Sa'dan
title_full_unstemmed	Automatic image annotation using color segmentation / Siti 'Aisyah Sa'dan
title_sort	automatic image annotation using color segmentation / siti 'aisyah sa'dan
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2009
url	https://ir.uitm.edu.my/id/eprint/87215/1/87215.pdf
_version_	1794192119728963584

Automatic image annotation using color segmentation / Siti 'Aisyah Sa'dan

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