Performance Evaluation of Completed Local Ternary Patterns (CLTP) for Medical, Scene and Event Image Categorisation

The Completed Local Ternary Pattern descriptor (CLTP) was proposed to overcome the drawbacks of the Local Binary Pattern (LBP). It used for rotation invariant texture classification and demonstrated superior classification accuracy with different types of texture datasets. In this paper, the perform...

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Main Authors:	Rassem, Taha H., Mohammed, Mohammed Falah, Khoo, Bee Ee, Makbol, Nasrin M.
Format:	Conference or Workshop Item
Language:	English
Published:	IEEE 2015
Subjects:	QA75 Electronic computers. Computer science QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/11453/ http://umpir.ump.edu.my/id/eprint/11453/ http://umpir.ump.edu.my/id/eprint/11453/ http://umpir.ump.edu.my/id/eprint/11453/7/Performance%20Evaluation%20of%20Completed%20Local%20Ternary%20Patterns%20cltp1.pdf

id	ump-11453
recordtype	eprints
spelling	ump-114532019-07-08T03:54:20Z http://umpir.ump.edu.my/id/eprint/11453/ Performance Evaluation of Completed Local Ternary Patterns (CLTP) for Medical, Scene and Event Image Categorisation Rassem, Taha H. Mohammed, Mohammed Falah Khoo, Bee Ee Makbol, Nasrin M. QA75 Electronic computers. Computer science QA76 Computer software The Completed Local Ternary Pattern descriptor (CLTP) was proposed to overcome the drawbacks of the Local Binary Pattern (LBP). It used for rotation invariant texture classification and demonstrated superior classification accuracy with different types of texture datasets. In this paper, the performance of CLTP for image categorisation is studied and investigated. Different image datasets are used in the experiments such as the Oliva and Torralba datasets (OT8), Event sport datasets, and 2D HeLa medical images. The experimental results proved the superiority of the CLTP descriptor over the original LBP, and different new texture descriptors such as Completed Local Binary Pattern (CLBP) in the image categorisation task. In 2D HeLa medical images, the proposed CLTP achieved the highest state of the art classification rate reaching 95.62% IEEE 2015-08-19 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/11453/7/Performance%20Evaluation%20of%20Completed%20Local%20Ternary%20Patterns%20cltp1.pdf Rassem, Taha H. and Mohammed, Mohammed Falah and Khoo, Bee Ee and Makbol, Nasrin M. (2015) Performance Evaluation of Completed Local Ternary Patterns (CLTP) for Medical, Scene and Event Image Categorisation. In: 4th International Conference on Software Engineering and Computer Systems (ICSECS 2015), 19-21 August 2015 , Kuantan, Pahang. pp. 33-38.. ISBN 978-1-4673-6722-6 http://dx.doi.org/10.1109/ICSECS.2015.7333119 doi:10.1109/ICSECS.2015.7333119
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA75 Electronic computers. Computer science QA76 Computer software
spellingShingle	QA75 Electronic computers. Computer science QA76 Computer software Rassem, Taha H. Mohammed, Mohammed Falah Khoo, Bee Ee Makbol, Nasrin M. Performance Evaluation of Completed Local Ternary Patterns (CLTP) for Medical, Scene and Event Image Categorisation
description	The Completed Local Ternary Pattern descriptor (CLTP) was proposed to overcome the drawbacks of the Local Binary Pattern (LBP). It used for rotation invariant texture classification and demonstrated superior classification accuracy with different types of texture datasets. In this paper, the performance of CLTP for image categorisation is studied and investigated. Different image datasets are used in the experiments such as the Oliva and Torralba datasets (OT8), Event sport datasets, and 2D HeLa medical images. The experimental results proved the superiority of the CLTP descriptor over the original LBP, and different new texture descriptors such as Completed Local Binary Pattern (CLBP) in the image categorisation task. In 2D HeLa medical images, the proposed CLTP achieved the highest state of the art classification rate reaching 95.62%
format	Conference or Workshop Item
author	Rassem, Taha H. Mohammed, Mohammed Falah Khoo, Bee Ee Makbol, Nasrin M.
author_facet	Rassem, Taha H. Mohammed, Mohammed Falah Khoo, Bee Ee Makbol, Nasrin M.
author_sort	Rassem, Taha H.
title	Performance Evaluation of Completed Local Ternary Patterns (CLTP) for Medical, Scene and Event Image Categorisation
title_short	Performance Evaluation of Completed Local Ternary Patterns (CLTP) for Medical, Scene and Event Image Categorisation
title_full	Performance Evaluation of Completed Local Ternary Patterns (CLTP) for Medical, Scene and Event Image Categorisation
title_fullStr	Performance Evaluation of Completed Local Ternary Patterns (CLTP) for Medical, Scene and Event Image Categorisation
title_full_unstemmed	Performance Evaluation of Completed Local Ternary Patterns (CLTP) for Medical, Scene and Event Image Categorisation
title_sort	performance evaluation of completed local ternary patterns (cltp) for medical, scene and event image categorisation
publisher	IEEE
publishDate	2015
url	http://umpir.ump.edu.my/id/eprint/11453/ http://umpir.ump.edu.my/id/eprint/11453/ http://umpir.ump.edu.my/id/eprint/11453/ http://umpir.ump.edu.my/id/eprint/11453/7/Performance%20Evaluation%20of%20Completed%20Local%20Ternary%20Patterns%20cltp1.pdf
first_indexed	2023-09-18T22:12:13Z
last_indexed	2023-09-18T22:12:13Z
_version_	1777415102869274624

Performance Evaluation of Completed Local Ternary Patterns (CLTP) for Medical, Scene and Event Image Categorisation

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