Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin

Underwater world had always been full of mystery in view of the fact that it was filled with unaccountably many species. Among the living organisms, fish are the most familiar to humans in environment, commercial and even recreational. From this perspective, fish recognition arouses interest of not...

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Main Author:	Nordin, Muhamad Syafiq
Format:	Thesis
Language:	English
Published:	2007
Online Access:	https://ir.uitm.edu.my/id/eprint/18276/2/TD_MUHAMAD%20SYAFIQ%20NORDIN%20CS%2007_5.pdf
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id	my-uitm-ir.18276
record_format	uketd_dc
spelling	my-uitm-ir.182762019-02-28T08:17:17Z Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin 2007 Nordin, Muhamad Syafiq Underwater world had always been full of mystery in view of the fact that it was filled with unaccountably many species. Among the living organisms, fish are the most familiar to humans in environment, commercial and even recreational. From this perspective, fish recognition arouses interest of not only dedicated underwater scientists but also of ordinary people who may be interested in this matter. Roughly 1.4 million species are known to science. Beyond this estimation, most unrecognized species are in poorly studied groups where it habitats were seldom explored. The job of discovering new species falls on the area of biology called taxonomy. The World-Wide Web is being used to collect data used by taxonomists’ for instance taxonomic literature and specimen databases in different parts of the globe, archived as digital images. This scenario had shown us that there is a need for an animal recognition tool that supports efficient searching and navigating through large image databases of specimens. In this research, a prototype of animal recognition application using Kohonen Feature Map was introduced. The system has a learning component that able to classify fish species based on the local visual feature of its representative image. This research also reveals Kohonen Feature Map as a promising tool for image classification. Realized that there is millions of species around the globe, this research focused on fish species that was common in Malaysia. 20 species were studied in this research. The image database used in the research was composed of 100 color images 2007 Thesis https://ir.uitm.edu.my/id/eprint/18276/ https://ir.uitm.edu.my/id/eprint/18276/2/TD_MUHAMAD%20SYAFIQ%20NORDIN%20CS%2007_5.pdf text en public dphil degree Universiti Teknologi MARA Faculty of Computer Science and Mathematics
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
description	Underwater world had always been full of mystery in view of the fact that it was filled with unaccountably many species. Among the living organisms, fish are the most familiar to humans in environment, commercial and even recreational. From this perspective, fish recognition arouses interest of not only dedicated underwater scientists but also of ordinary people who may be interested in this matter. Roughly 1.4 million species are known to science. Beyond this estimation, most unrecognized species are in poorly studied groups where it habitats were seldom explored. The job of discovering new species falls on the area of biology called taxonomy. The World-Wide Web is being used to collect data used by taxonomists’ for instance taxonomic literature and specimen databases in different parts of the globe, archived as digital images. This scenario had shown us that there is a need for an animal recognition tool that supports efficient searching and navigating through large image databases of specimens. In this research, a prototype of animal recognition application using Kohonen Feature Map was introduced. The system has a learning component that able to classify fish species based on the local visual feature of its representative image. This research also reveals Kohonen Feature Map as a promising tool for image classification. Realized that there is millions of species around the globe, this research focused on fish species that was common in Malaysia. 20 species were studied in this research. The image database used in the research was composed of 100 color images
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Bachelor degree
author	Nordin, Muhamad Syafiq
spellingShingle	Nordin, Muhamad Syafiq Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin
author_facet	Nordin, Muhamad Syafiq
author_sort	Nordin, Muhamad Syafiq
title	Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin
title_short	Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin
title_full	Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin
title_fullStr	Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin
title_full_unstemmed	Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin
title_sort	animal recognition application using kohonen feature map / muhamad syafiq nordin
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Computer Science and Mathematics
publishDate	2007
url	https://ir.uitm.edu.my/id/eprint/18276/2/TD_MUHAMAD%20SYAFIQ%20NORDIN%20CS%2007_5.pdf
_version_	1783733649432117248

Animal recognition application using Kohonen Feature Map / Muhamad Syafiq Nordin

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