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

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.

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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 %.

Item Type: Conference or Workshop Item (Invited Papers)
Additional Information: 2470/42180 (ISBN: 978-1-4799-7635-5, DOI: 10.1109/ICCCE.2014.37)
Uncontrolled Keywords: Classification; Order moments; Principal Component Analysis (PCA); Retinal images; Sequential Minimal Optimization (SMO)
Subjects: Q Science > Q Science (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Depositing User: Prof Momoh-Jimoh Salami
Date Deposited: 19 Mar 2015 15:26
Last Modified: 20 Sep 2017 20:28
URI: http://irep.iium.edu.my/id/eprint/42180

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