Overlapped and shadowed tree crown segmentation based on HSI color model and watershed algoritim

Image provides valuable information to the human and this information could be used to take an effective dissection such as information that comes from satellite sensors. Satellite images let the human have the information from the ground for very wide area. The negative side of satellite image is t...

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Bibliographic Details
Main Author:	Mohamed Arrish, Senosy Suliman
Format:	Thesis
Language:	English
Published:	2014
Subjects:	G Geography Anthropology Recreation
Online Access:	http://eprints.utm.my/id/eprint/41690/1/SenosySulimanMohamedArrishMFSKSM2014.pdf
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id	my-utm-ep.41690
record_format	uketd_dc
spelling	my-utm-ep.416902017-09-10T08:22:44Z Overlapped and shadowed tree crown segmentation based on HSI color model and watershed algoritim 2014-01 Mohamed Arrish, Senosy Suliman G Geography. Anthropology. Recreation Image provides valuable information to the human and this information could be used to take an effective dissection such as information that comes from satellite sensors. Satellite images let the human have the information from the ground for very wide area. The negative side of satellite image is the resolution is still not much high. Satellite image play a vital role in many area of our live, especially agriculture, where the human can calculate the crown of the tree for very wide area in very short time. The counting of tree will not be accurate without getting good segmentation of these crowns. This work has applied segmentation algorithm to separate crown of coconut palm tree from shadow and the overlapped crown as well. The algorithm has exploited HSI color model to differentiate the color of crown from the color of shadow. The result of using this feature gives very different color for both shadow and crown. After crown detection the algorithm used morphological operation such as image filling to enhance the crown. The following step is removing noise or pixels which considered unwanted objects. Finally, the image was segmented using watershed after applying distance transform on the image. Since this research does not has ground information to measure the accuracy, the evaluation has been done manually, where the crown has counted manually and calculate the accuracy of this work which is 73%. 2014-01 Thesis http://eprints.utm.my/id/eprint/41690/ http://eprints.utm.my/id/eprint/41690/1/SenosySulimanMohamedArrishMFSKSM2014.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computing Faculty of Computing
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	G Geography Anthropology Recreation
spellingShingle	G Geography Anthropology Recreation Mohamed Arrish, Senosy Suliman Overlapped and shadowed tree crown segmentation based on HSI color model and watershed algoritim
description	Image provides valuable information to the human and this information could be used to take an effective dissection such as information that comes from satellite sensors. Satellite images let the human have the information from the ground for very wide area. The negative side of satellite image is the resolution is still not much high. Satellite image play a vital role in many area of our live, especially agriculture, where the human can calculate the crown of the tree for very wide area in very short time. The counting of tree will not be accurate without getting good segmentation of these crowns. This work has applied segmentation algorithm to separate crown of coconut palm tree from shadow and the overlapped crown as well. The algorithm has exploited HSI color model to differentiate the color of crown from the color of shadow. The result of using this feature gives very different color for both shadow and crown. After crown detection the algorithm used morphological operation such as image filling to enhance the crown. The following step is removing noise or pixels which considered unwanted objects. Finally, the image was segmented using watershed after applying distance transform on the image. Since this research does not has ground information to measure the accuracy, the evaluation has been done manually, where the crown has counted manually and calculate the accuracy of this work which is 73%.
format	Thesis
qualification_level	Master's degree
author	Mohamed Arrish, Senosy Suliman
author_facet	Mohamed Arrish, Senosy Suliman
author_sort	Mohamed Arrish, Senosy Suliman
title	Overlapped and shadowed tree crown segmentation based on HSI color model and watershed algoritim
title_short	Overlapped and shadowed tree crown segmentation based on HSI color model and watershed algoritim
title_full	Overlapped and shadowed tree crown segmentation based on HSI color model and watershed algoritim
title_fullStr	Overlapped and shadowed tree crown segmentation based on HSI color model and watershed algoritim
title_full_unstemmed	Overlapped and shadowed tree crown segmentation based on HSI color model and watershed algoritim
title_sort	overlapped and shadowed tree crown segmentation based on hsi color model and watershed algoritim
granting_institution	Universiti Teknologi Malaysia, Faculty of Computing
granting_department	Faculty of Computing
publishDate	2014
url	http://eprints.utm.my/id/eprint/41690/1/SenosySulimanMohamedArrishMFSKSM2014.pdf
_version_	1747816597732458496

Overlapped and shadowed tree crown segmentation based on HSI color model and watershed algoritim

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