Automatic classification and recognition of coral reefs from underwater video images

This thesis presents a new approach to automate the classification and estimation of coral reef based on computer vision techniques by performing classification and recognition on digitized video obtained from surrounding reef ecosystem. By knowing the state of the coral reefs, marine scientist ca...

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Main Author: Leng, Wong Siew
Format: Thesis
Language:English
Published: Fakulti Sains dan Teknologi 2011
Subjects:
Online Access:http://hdl.handle.net/123456789/744
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id my.umt.ir-744
record_format eprints
spelling my.umt.ir-7442016-03-10T03:45:29Z Automatic classification and recognition of coral reefs from underwater video images Leng, Wong Siew QH 541.5 .C7 L4 2006 Leng, Wong Siew Automatic classification and recognition of coral reefs from underwater video images Coral reefs This thesis presents a new approach to automate the classification and estimation of coral reef based on computer vision techniques by performing classification and recognition on digitized video obtained from surrounding reef ecosystem. By knowing the state of the coral reefs, marine scientist can predict fish yield or determine how the reef system is coping with the environment in a less tedious and less time consuming way. In this project, the objective is to classify and recognize a predetermined reef benthos groups. These groups are alive coral, dead coral, sand and rubble. As for the alive coral group, possible higher level of taxonomic classification is performed to discriminate the classes of branching, digitate and tabulate solely based on digital video recording. 2011-05-31T07:54:41Z 2011-05-31T07:54:41Z 2006-10 Thesis http://hdl.handle.net/123456789/744 en application/pdf application/pdf Fakulti Sains dan Teknologi
institution Universiti Malaysia Terengganu
building Perpustakaan Sultanah Nur Zahirah
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Terengganu
content_source UMT-IR
url_provider http://umt-ir.umt.edu.my:8080/
language English
topic QH 541.5 .C7 L4 2006
Leng, Wong Siew
Automatic classification and recognition of coral reefs from underwater video images
Coral reefs
spellingShingle QH 541.5 .C7 L4 2006
Leng, Wong Siew
Automatic classification and recognition of coral reefs from underwater video images
Coral reefs
Leng, Wong Siew
Automatic classification and recognition of coral reefs from underwater video images
description This thesis presents a new approach to automate the classification and estimation of coral reef based on computer vision techniques by performing classification and recognition on digitized video obtained from surrounding reef ecosystem. By knowing the state of the coral reefs, marine scientist can predict fish yield or determine how the reef system is coping with the environment in a less tedious and less time consuming way. In this project, the objective is to classify and recognize a predetermined reef benthos groups. These groups are alive coral, dead coral, sand and rubble. As for the alive coral group, possible higher level of taxonomic classification is performed to discriminate the classes of branching, digitate and tabulate solely based on digital video recording.
format Thesis
author Leng, Wong Siew
author_facet Leng, Wong Siew
author_sort Leng, Wong Siew
title Automatic classification and recognition of coral reefs from underwater video images
title_short Automatic classification and recognition of coral reefs from underwater video images
title_full Automatic classification and recognition of coral reefs from underwater video images
title_fullStr Automatic classification and recognition of coral reefs from underwater video images
title_full_unstemmed Automatic classification and recognition of coral reefs from underwater video images
title_sort automatic classification and recognition of coral reefs from underwater video images
publisher Fakulti Sains dan Teknologi
publishDate 2011
url http://hdl.handle.net/123456789/744
_version_ 1738395544386011136
score 13.160551