A new feature extraction algorithm for overlapping leaves of rubber tree

Rubber is one of the major sources of national income in Malaysia. Malaysian Rubber Board (MRB) is responsible for the monitoring the quality of rubber to maintain a successful rubber clone breeding program. One of the important factors that affect the quality of raw rubber is the clonal origin of t...

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Main Author:	Anjomshoae, Sule
Format:	Thesis
Language:	English
Published:	2014
Subjects:	TK7885-7895 Computer engineer Computer hardware
Online Access:	http://eprints.utm.my/id/eprint/48000/25/SuleAnjomshoaeMFC2014.pdf
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id	my-utm-ep.48000
record_format	uketd_dc
spelling	my-utm-ep.480002017-08-11T05:26:43Z A new feature extraction algorithm for overlapping leaves of rubber tree 2014-05 Anjomshoae, Sule TK7885-7895 Computer engineer. Computer hardware Rubber is one of the major sources of national income in Malaysia. Malaysian Rubber Board (MRB) is responsible for the monitoring the quality of rubber to maintain a successful rubber clone breeding program. One of the important factors that affect the quality of raw rubber is the clonal origin of the rubber tree. Currently, clone inspectors classify the rubber tree clones manually using leaf features. There are several features such as leaf tip, leaf base to identify the type of clone. An automated clone classification process is needed to facilitate the inspection process. This research focuses on extracting one of the features for identifying clones which are overlapping leaf features. The challenge of overlapping leaf identification is the similarity of the intensity levels. However, it can be classified using shape and angle of leaves. Therefore, a new feature extraction framework is required to extract shape and angle features. In the new framework, key point extraction method is combined with the nearest neighbor algorithm to extract shape feature. While, angle feature is developed using Hough transform. The proposed method able to detect edge, ridge, and blob features and identify angle between petioles of overlapping leaves. This study identified that angle degrees of the overlapping leaves are in the range between 30° and 55° while angle degrees of non-overlapping leaves are in the range between 55° and 90°. In order to validate the result, the identification method has been tested with fifty rubber leaf images that comprise of both overlapping and non-overlapping features images. The results indicated that forty six overlapping and non-overlapping leaf images matched successfully with correct templates. As a conclusion, the proposed features and their extraction method can be used to identify overlapping and non-overlapping rubber tree leaves. 2014-05 Thesis http://eprints.utm.my/id/eprint/48000/ http://eprints.utm.my/id/eprint/48000/25/SuleAnjomshoaeMFC2014.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	TK7885-7895 Computer engineer Computer hardware
spellingShingle	TK7885-7895 Computer engineer Computer hardware Anjomshoae, Sule A new feature extraction algorithm for overlapping leaves of rubber tree
description	Rubber is one of the major sources of national income in Malaysia. Malaysian Rubber Board (MRB) is responsible for the monitoring the quality of rubber to maintain a successful rubber clone breeding program. One of the important factors that affect the quality of raw rubber is the clonal origin of the rubber tree. Currently, clone inspectors classify the rubber tree clones manually using leaf features. There are several features such as leaf tip, leaf base to identify the type of clone. An automated clone classification process is needed to facilitate the inspection process. This research focuses on extracting one of the features for identifying clones which are overlapping leaf features. The challenge of overlapping leaf identification is the similarity of the intensity levels. However, it can be classified using shape and angle of leaves. Therefore, a new feature extraction framework is required to extract shape and angle features. In the new framework, key point extraction method is combined with the nearest neighbor algorithm to extract shape feature. While, angle feature is developed using Hough transform. The proposed method able to detect edge, ridge, and blob features and identify angle between petioles of overlapping leaves. This study identified that angle degrees of the overlapping leaves are in the range between 30° and 55° while angle degrees of non-overlapping leaves are in the range between 55° and 90°. In order to validate the result, the identification method has been tested with fifty rubber leaf images that comprise of both overlapping and non-overlapping features images. The results indicated that forty six overlapping and non-overlapping leaf images matched successfully with correct templates. As a conclusion, the proposed features and their extraction method can be used to identify overlapping and non-overlapping rubber tree leaves.
format	Thesis
qualification_level	Master's degree
author	Anjomshoae, Sule
author_facet	Anjomshoae, Sule
author_sort	Anjomshoae, Sule
title	A new feature extraction algorithm for overlapping leaves of rubber tree
title_short	A new feature extraction algorithm for overlapping leaves of rubber tree
title_full	A new feature extraction algorithm for overlapping leaves of rubber tree
title_fullStr	A new feature extraction algorithm for overlapping leaves of rubber tree
title_full_unstemmed	A new feature extraction algorithm for overlapping leaves of rubber tree
title_sort	new feature extraction algorithm for overlapping leaves of rubber tree
granting_institution	Universiti Teknologi Malaysia, Faculty of Computing
granting_department	Faculty of Computing
publishDate	2014
url	http://eprints.utm.my/id/eprint/48000/25/SuleAnjomshoaeMFC2014.pdf
_version_	1747817283388964864

A new feature extraction algorithm for overlapping leaves of rubber tree

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