EFA for Structure Detection in Image Data : Empirical Results on Two Datasets of Different Perspective

Structure detection discovery from image data is scarce. Hence, we attempt to explore and uncover the underlying structure from two datasets of different perspective through statistical procedures commonly used in psychology, social science, health and business. Firstly, distinction between princip...

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Main Authors: Lim, Phei-Chin, Kulathuramaiyer, Narayanan, Awang Iskandar, D.N.F., Chiew, Kang Leng
Format: Proceeding
Language:English
Published: 2015
Subjects:
Online Access:http://ir.unimas.my/id/eprint/13443/
http://ir.unimas.my/id/eprint/13443/1/EFA%20for%20Structure%20Detection%20in%20Image%20Data%20%28abstract%29.pdf
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author Lim, Phei-Chin
Kulathuramaiyer, Narayanan
Awang Iskandar, D.N.F.
Chiew, Kang Leng
author_facet Lim, Phei-Chin
Kulathuramaiyer, Narayanan
Awang Iskandar, D.N.F.
Chiew, Kang Leng
author_sort Lim, Phei-Chin
building UNIMAS Institutional Repository
collection Online Access
description Structure detection discovery from image data is scarce. Hence, we attempt to explore and uncover the underlying structure from two datasets of different perspective through statistical procedures commonly used in psychology, social science, health and business. Firstly, distinction between principal component analysis and exploratory factor analysis are briefly described; along with a simple test on the growth of publications on both techniques and datasets tested in this paper. Exploratory factor analyses results with and without data screening are summarized. 3-factor structures are derived from both datasets where texture features seem to be dominant than others. Some critical issues concerning the appropriateness of methods are also discussed. The systematic procedures described in this paper are applicable to any other object type with similar characteristics as the ones tested.
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institution Universiti Malaysia Sarawak
institution_category Local University
language English
last_indexed 2025-11-15T06:39:12Z
publishDate 2015
recordtype eprints
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spelling unimas-134432017-02-14T05:37:58Z http://ir.unimas.my/id/eprint/13443/ EFA for Structure Detection in Image Data : Empirical Results on Two Datasets of Different Perspective Lim, Phei-Chin Kulathuramaiyer, Narayanan Awang Iskandar, D.N.F. Chiew, Kang Leng T Technology (General) Structure detection discovery from image data is scarce. Hence, we attempt to explore and uncover the underlying structure from two datasets of different perspective through statistical procedures commonly used in psychology, social science, health and business. Firstly, distinction between principal component analysis and exploratory factor analysis are briefly described; along with a simple test on the growth of publications on both techniques and datasets tested in this paper. Exploratory factor analyses results with and without data screening are summarized. 3-factor structures are derived from both datasets where texture features seem to be dominant than others. Some critical issues concerning the appropriateness of methods are also discussed. The systematic procedures described in this paper are applicable to any other object type with similar characteristics as the ones tested. 2015 Proceeding PeerReviewed text en http://ir.unimas.my/id/eprint/13443/1/EFA%20for%20Structure%20Detection%20in%20Image%20Data%20%28abstract%29.pdf Lim, Phei-Chin and Kulathuramaiyer, Narayanan and Awang Iskandar, D.N.F. and Chiew, Kang Leng (2015) EFA for Structure Detection in Image Data : Empirical Results on Two Datasets of Different Perspective. In: 2015 9th International Conference on IT in Asia (CITA) : Transforming Big Data into Knowledge, 4-5 August 2015, Kuching, Sarawak Malaysia.
spellingShingle T Technology (General)
Lim, Phei-Chin
Kulathuramaiyer, Narayanan
Awang Iskandar, D.N.F.
Chiew, Kang Leng
EFA for Structure Detection in Image Data : Empirical Results on Two Datasets of Different Perspective
title EFA for Structure Detection in Image Data : Empirical Results on Two Datasets of Different Perspective
title_full EFA for Structure Detection in Image Data : Empirical Results on Two Datasets of Different Perspective
title_fullStr EFA for Structure Detection in Image Data : Empirical Results on Two Datasets of Different Perspective
title_full_unstemmed EFA for Structure Detection in Image Data : Empirical Results on Two Datasets of Different Perspective
title_short EFA for Structure Detection in Image Data : Empirical Results on Two Datasets of Different Perspective
title_sort efa for structure detection in image data : empirical results on two datasets of different perspective
topic T Technology (General)
url http://ir.unimas.my/id/eprint/13443/
http://ir.unimas.my/id/eprint/13443/1/EFA%20for%20Structure%20Detection%20in%20Image%20Data%20%28abstract%29.pdf