Development of real-time pose estimation algorithm for Quranic Arabic word

The study carried out in this report proposes the best keypoint detection, description, and pose estimation algorithm combination for Quranic Arabic words. Oriented-FAST Rotated-BRIEF (ORB) and Accelerated-KAZE (AKAZE) are used as the keypoint detection and description algorithms while Random Sample...

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Main Authors:	Mohd Esa, Luqman Naim, Morshidi, Malik Arman, Mohd Zailani, Syarah Munirah
Format:	Article
Language:	English English English
Published:	Institute of Advanced Engineering and Science (IAES) 2017
Subjects:	QA75 Electronic computers. Computer science QA76 Computer software
Online Access:	http://irep.iium.edu.my/60356/ http://irep.iium.edu.my/60356/3/AcceptanceEmail.pdf http://irep.iium.edu.my/60356/9/60356_Development%20of%20real-time%20pose%20estimation%20algorithm%20.pdf http://irep.iium.edu.my/60356/15/60356_Development%20of%20real-time%20pose%20estimation%20algorithm%20for%20Quranic%20Arabic%20word_scopus.pdf

id	iium-60356
recordtype	eprints
spelling	iium-603562019-08-22T04:48:09Z http://irep.iium.edu.my/60356/ Development of real-time pose estimation algorithm for Quranic Arabic word Mohd Esa, Luqman Naim Morshidi, Malik Arman Mohd Zailani, Syarah Munirah QA75 Electronic computers. Computer science QA76 Computer software The study carried out in this report proposes the best keypoint detection, description, and pose estimation algorithm combination for Quranic Arabic words. Oriented-FAST Rotated-BRIEF (ORB) and Accelerated-KAZE (AKAZE) are used as the keypoint detection and description algorithms while Random Sample Consensus (RANSAC) and Least Median Squares (LMEDS) are used to evaluate the homography for pose estimation algorithms. The algorithms are combined with each other to provide four different techniques to estimate the pose of Quranic Arabic words. The algorithms are tested on a limited dataset chosen from a phrase within the Quran. Performance of each algorithm is measured in real-time through inlier to keypoint ratio which determines pose accuracy. Institute of Advanced Engineering and Science (IAES) 2017-12-05 Article PeerReviewed application/pdf en http://irep.iium.edu.my/60356/3/AcceptanceEmail.pdf application/pdf en http://irep.iium.edu.my/60356/9/60356_Development%20of%20real-time%20pose%20estimation%20algorithm%20.pdf application/pdf en http://irep.iium.edu.my/60356/15/60356_Development%20of%20real-time%20pose%20estimation%20algorithm%20for%20Quranic%20Arabic%20word_scopus.pdf Mohd Esa, Luqman Naim and Morshidi, Malik Arman and Mohd Zailani, Syarah Munirah (2017) Development of real-time pose estimation algorithm for Quranic Arabic word. Indonesian Journal of Electrical Engineering and Computer Science. ISSN 2502-4760 E-ISSN 2502-4760 (In Press)
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English English
topic	QA75 Electronic computers. Computer science QA76 Computer software
spellingShingle	QA75 Electronic computers. Computer science QA76 Computer software Mohd Esa, Luqman Naim Morshidi, Malik Arman Mohd Zailani, Syarah Munirah Development of real-time pose estimation algorithm for Quranic Arabic word
description	The study carried out in this report proposes the best keypoint detection, description, and pose estimation algorithm combination for Quranic Arabic words. Oriented-FAST Rotated-BRIEF (ORB) and Accelerated-KAZE (AKAZE) are used as the keypoint detection and description algorithms while Random Sample Consensus (RANSAC) and Least Median Squares (LMEDS) are used to evaluate the homography for pose estimation algorithms. The algorithms are combined with each other to provide four different techniques to estimate the pose of Quranic Arabic words. The algorithms are tested on a limited dataset chosen from a phrase within the Quran. Performance of each algorithm is measured in real-time through inlier to keypoint ratio which determines pose accuracy.
format	Article
author	Mohd Esa, Luqman Naim Morshidi, Malik Arman Mohd Zailani, Syarah Munirah
author_facet	Mohd Esa, Luqman Naim Morshidi, Malik Arman Mohd Zailani, Syarah Munirah
author_sort	Mohd Esa, Luqman Naim
title	Development of real-time pose estimation algorithm for Quranic Arabic word
title_short	Development of real-time pose estimation algorithm for Quranic Arabic word
title_full	Development of real-time pose estimation algorithm for Quranic Arabic word
title_fullStr	Development of real-time pose estimation algorithm for Quranic Arabic word
title_full_unstemmed	Development of real-time pose estimation algorithm for Quranic Arabic word
title_sort	development of real-time pose estimation algorithm for quranic arabic word
publisher	Institute of Advanced Engineering and Science (IAES)
publishDate	2017
url	http://irep.iium.edu.my/60356/ http://irep.iium.edu.my/60356/3/AcceptanceEmail.pdf http://irep.iium.edu.my/60356/9/60356_Development%20of%20real-time%20pose%20estimation%20algorithm%20.pdf http://irep.iium.edu.my/60356/15/60356_Development%20of%20real-time%20pose%20estimation%20algorithm%20for%20Quranic%20Arabic%20word_scopus.pdf
first_indexed	2023-09-18T21:25:33Z
last_indexed	2023-09-18T21:25:33Z
_version_	1777412167500300288

Development of real-time pose estimation algorithm for Quranic Arabic word

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