Classification of retinal images based on statistical moments and principal component analysis

Early diagnosis of Diabetic Retinopathy (DR) has been suggested as a good measure of preventing blindness associated with Diabetes. Some of the reported methodologies of Retinal Images (RI) classification for early diagnosis of DR have been shown to involve several steps and approaches for effective...

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Main Authors:	Salami, Momoh Jimoh Emiyoka, Khorshidtalab, A., Baali, Hamza, Aibinu, Abiodun Musa
Format:	Conference or Workshop Item
Language:	English English
Published:	IEEE 2014
Subjects:	Q Science (General)
Online Access:	http://irep.iium.edu.my/42180/ http://irep.iium.edu.my/42180/ http://irep.iium.edu.my/42180/ http://irep.iium.edu.my/42180/1/42180_edited.pdf http://irep.iium.edu.my/42180/4/42180_Classification%20of%20retinal%20images%20based%20on%20statistical_Scopus.pdf

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recordtype	eprints
spelling	iium-421802017-09-20T12:28:23Z http://irep.iium.edu.my/42180/ Classification of retinal images based on statistical moments and principal component analysis Salami, Momoh Jimoh Emiyoka Khorshidtalab, A. Baali, Hamza Aibinu, Abiodun Musa Q Science (General) Early diagnosis of Diabetic Retinopathy (DR) has been suggested as a good measure of preventing blindness associated with Diabetes. Some of the reported methodologies of Retinal Images (RI) classification for early diagnosis of DR have been shown to involve several steps and approaches for effective and accurate diagnosis. Thus, this paper investigates the classification of RI using a two-stage procedure. The first stage includes the extraction of blood vessels from RI belonging to healthy and diabetes retinal images using a modified local entropy thresholding algorithm. In the second stage, different features are extracted including statistical moments and principal components. The set of extracted features is combined into one feature vector and fed into a Sequential Minimal Optimization (SMO) classifier. The obtained result is encouraging with an average accuracy of 68.33 %. IEEE 2014 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/42180/1/42180_edited.pdf application/pdf en http://irep.iium.edu.my/42180/4/42180_Classification%20of%20retinal%20images%20based%20on%20statistical_Scopus.pdf Salami, Momoh Jimoh Emiyoka and Khorshidtalab, A. and Baali, Hamza and Aibinu, Abiodun Musa (2014) Classification of retinal images based on statistical moments and principal component analysis. In: 5th International Conference on Computer and Communication Engineering (ICCCE 2014), 23th - 25th September 2014, Sunway Putra Hotel, Kuala Lumpur. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7031608 10.1109/ICCCE.2014.37
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	Q Science (General)
spellingShingle	Q Science (General) Salami, Momoh Jimoh Emiyoka Khorshidtalab, A. Baali, Hamza Aibinu, Abiodun Musa Classification of retinal images based on statistical moments and principal component analysis
description	Early diagnosis of Diabetic Retinopathy (DR) has been suggested as a good measure of preventing blindness associated with Diabetes. Some of the reported methodologies of Retinal Images (RI) classification for early diagnosis of DR have been shown to involve several steps and approaches for effective and accurate diagnosis. Thus, this paper investigates the classification of RI using a two-stage procedure. The first stage includes the extraction of blood vessels from RI belonging to healthy and diabetes retinal images using a modified local entropy thresholding algorithm. In the second stage, different features are extracted including statistical moments and principal components. The set of extracted features is combined into one feature vector and fed into a Sequential Minimal Optimization (SMO) classifier. The obtained result is encouraging with an average accuracy of 68.33 %.
format	Conference or Workshop Item
author	Salami, Momoh Jimoh Emiyoka Khorshidtalab, A. Baali, Hamza Aibinu, Abiodun Musa
author_facet	Salami, Momoh Jimoh Emiyoka Khorshidtalab, A. Baali, Hamza Aibinu, Abiodun Musa
author_sort	Salami, Momoh Jimoh Emiyoka
title	Classification of retinal images based on statistical moments and principal component analysis
title_short	Classification of retinal images based on statistical moments and principal component analysis
title_full	Classification of retinal images based on statistical moments and principal component analysis
title_fullStr	Classification of retinal images based on statistical moments and principal component analysis
title_full_unstemmed	Classification of retinal images based on statistical moments and principal component analysis
title_sort	classification of retinal images based on statistical moments and principal component analysis
publisher	IEEE
publishDate	2014
url	http://irep.iium.edu.my/42180/ http://irep.iium.edu.my/42180/ http://irep.iium.edu.my/42180/ http://irep.iium.edu.my/42180/1/42180_edited.pdf http://irep.iium.edu.my/42180/4/42180_Classification%20of%20retinal%20images%20based%20on%20statistical_Scopus.pdf
first_indexed	2023-09-18T21:00:11Z
last_indexed	2023-09-18T21:00:11Z
_version_	1777410571275075584

Classification of retinal images based on statistical moments and principal component analysis

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