Image clustering of songket motif / Zuharabih Sulaiman

Songket is fabric which belongs to the brocade family of textiles. It is hand woven in silk or cotton, and intricately patterned with gold or silver threads. The important factor of designing songket pattern is the motif Motifs are used to design the songket pattern and they are usually arranged in...

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Main Author:	Sulaiman, Zuharabih
Format:	Thesis
Language:	English
Published:	2007
Subjects:	Weaving and spinning Textile fabrics Special subjects for design
Online Access:	https://ir.uitm.edu.my/id/eprint/87183/1/87183.pdf
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id	my-uitm-ir.87183
record_format	uketd_dc
spelling	my-uitm-ir.871832024-02-19T02:18:29Z Image clustering of songket motif / Zuharabih Sulaiman 2007 Sulaiman, Zuharabih Weaving and spinning. Textile fabrics Special subjects for design Songket is fabric which belongs to the brocade family of textiles. It is hand woven in silk or cotton, and intricately patterned with gold or silver threads. The important factor of designing songket pattern is the motif Motifs are used to design the songket pattern and they are usually arranged in such a way that they look like several chains linked together rand one main motif in between the chains. A songket pattern consist of thousands of motifs, it could be the same motifs of mixed motifs. This paper describe and compares three methods of image clustering methods to determine which methods is the best method by doing the performance measurement on each of the methods, implement the best methods and test the prototype. Even though there are many methods are applicable to cluster an image, only three methods are chosen that is Fuzzy C-means clustering, K means clustering and hierarchical clustering. These three method's cluster result will be compared in order to choose the most acceptable method to be implemented in developing the clustering tool. Two hundred eighty nine motifs will be used as the data samples in this paper. These songket motifs are clustered based on its five basic shapes feature which are eccentricity, compactness, convexity, rectangularity, and solidity. The clustering method that provides the most acceptable result is K-means clustering and the prototype development is done by adapting the K-means clustering concept in it. Result of the clusters assigned to each of the motifs was manually compared with the actual clusters assigned manually to the motifs. The result produced by the prototype is thirty six percent of correctness and sixty four percent of incorrectness when assigning motifs into clusters. 2007 Thesis https://ir.uitm.edu.my/id/eprint/87183/ https://ir.uitm.edu.my/id/eprint/87183/1/87183.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
topic	Weaving and spinning Textile fabrics Special subjects for design
spellingShingle	Weaving and spinning Textile fabrics Special subjects for design Sulaiman, Zuharabih Image clustering of songket motif / Zuharabih Sulaiman
description	Songket is fabric which belongs to the brocade family of textiles. It is hand woven in silk or cotton, and intricately patterned with gold or silver threads. The important factor of designing songket pattern is the motif Motifs are used to design the songket pattern and they are usually arranged in such a way that they look like several chains linked together rand one main motif in between the chains. A songket pattern consist of thousands of motifs, it could be the same motifs of mixed motifs. This paper describe and compares three methods of image clustering methods to determine which methods is the best method by doing the performance measurement on each of the methods, implement the best methods and test the prototype. Even though there are many methods are applicable to cluster an image, only three methods are chosen that is Fuzzy C-means clustering, K means clustering and hierarchical clustering. These three method's cluster result will be compared in order to choose the most acceptable method to be implemented in developing the clustering tool. Two hundred eighty nine motifs will be used as the data samples in this paper. These songket motifs are clustered based on its five basic shapes feature which are eccentricity, compactness, convexity, rectangularity, and solidity. The clustering method that provides the most acceptable result is K-means clustering and the prototype development is done by adapting the K-means clustering concept in it. Result of the clusters assigned to each of the motifs was manually compared with the actual clusters assigned manually to the motifs. The result produced by the prototype is thirty six percent of correctness and sixty four percent of incorrectness when assigning motifs into clusters.
format	Thesis
qualification_level	Bachelor degree
author	Sulaiman, Zuharabih
author_facet	Sulaiman, Zuharabih
author_sort	Sulaiman, Zuharabih
title	Image clustering of songket motif / Zuharabih Sulaiman
title_short	Image clustering of songket motif / Zuharabih Sulaiman
title_full	Image clustering of songket motif / Zuharabih Sulaiman
title_fullStr	Image clustering of songket motif / Zuharabih Sulaiman
title_full_unstemmed	Image clustering of songket motif / Zuharabih Sulaiman
title_sort	image clustering of songket motif / zuharabih sulaiman
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2007
url	https://ir.uitm.edu.my/id/eprint/87183/1/87183.pdf
_version_	1794192117336113152

Image clustering of songket motif / Zuharabih Sulaiman

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