Early rubeosis iridis detection using feature extraction process

Iris analytical studies the relationship between human health and changes in the anatomy of the iris. One of the related to the changes of the anat-omy of the iris is diabetic. Diabetic illness can be determine from the iris of hu-man eyes because it’s affects the eyes. Latest advance technologies a...

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Main Authors:	Rohana, Abdul Karim, Nur Amira Adila, Abd Mobin, Nurul Wahidah, Arshad, Nor Farizan, Zakaria, M. Zabri, Abu Bakar
Format:	Conference or Workshop Item
Language:	English English
Published:	Universiti Malaysia Pahang 2019
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/26666/ http://umpir.ump.edu.my/id/eprint/26666/1/27.%20Early%20rubeosis%20iridis%20detection%20using%20feature%20extraction%20process.pdf http://umpir.ump.edu.my/id/eprint/26666/2/27.1%20Early%20rubeosis%20iridis%20detection%20using%20feature%20extraction%20process.pdf

id	ump-26666
recordtype	eprints
spelling	ump-266662019-12-23T08:23:41Z http://umpir.ump.edu.my/id/eprint/26666/ Early rubeosis iridis detection using feature extraction process Rohana, Abdul Karim Nur Amira Adila, Abd Mobin Nurul Wahidah, Arshad Nor Farizan, Zakaria M. Zabri, Abu Bakar TK Electrical engineering. Electronics Nuclear engineering Iris analytical studies the relationship between human health and changes in the anatomy of the iris. One of the related to the changes of the anat-omy of the iris is diabetic. Diabetic illness can be determine from the iris of hu-man eyes because it’s affects the eyes. Latest advance technologies are intro-duced in the image processing that helps automate detection of diabetic in iris based on the analysis of feature extractions. This analysis not only helps diagnose the disease, besides its helps detect the disease. Various features are detected on iris such as texture, colour, histogram and shape features. In this paper, the dataset of iris image is use to detect and recognise the rubeosis iridis. To detect and rec-ognize the rubeosis iridis, it needs to extract the detail of the image of iris using image processing methods. In this paper, the proposed method is to detect and recognize the rubeosis iridis by using the feature extraction and the datasets used for this project is Warsaw Biobase. Finally, the rubeosis iridis is detected and the proposed method is discussed on this paper. The results obtained from the exper-iment show that the normal and abnormal iris image can be classified using orig-inal and small size of iris image. In this experiment, abnormal original are greater than 1200000 pixel while for small size are less than 35000 pixel. Normal origi-nal size which is less than 1200000 pixel and for small are less than 25000 pixel. By considering this result, the proposed method can be extended to the iris mon-itoring system. Universiti Malaysia Pahang 2019 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/26666/1/27.%20Early%20rubeosis%20iridis%20detection%20using%20feature%20extraction%20process.pdf pdf en http://umpir.ump.edu.my/id/eprint/26666/2/27.1%20Early%20rubeosis%20iridis%20detection%20using%20feature%20extraction%20process.pdf Rohana, Abdul Karim and Nur Amira Adila, Abd Mobin and Nurul Wahidah, Arshad and Nor Farizan, Zakaria and M. Zabri, Abu Bakar (2019) Early rubeosis iridis detection using feature extraction process. In: 5th International Conference on Electrical, Control and Computer Engineering (INECCE 2019), 29-30 July 2019 , Swiss Garden Kuantan. pp. 1-10.. (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Rohana, Abdul Karim Nur Amira Adila, Abd Mobin Nurul Wahidah, Arshad Nor Farizan, Zakaria M. Zabri, Abu Bakar Early rubeosis iridis detection using feature extraction process
description	Iris analytical studies the relationship between human health and changes in the anatomy of the iris. One of the related to the changes of the anat-omy of the iris is diabetic. Diabetic illness can be determine from the iris of hu-man eyes because it’s affects the eyes. Latest advance technologies are intro-duced in the image processing that helps automate detection of diabetic in iris based on the analysis of feature extractions. This analysis not only helps diagnose the disease, besides its helps detect the disease. Various features are detected on iris such as texture, colour, histogram and shape features. In this paper, the dataset of iris image is use to detect and recognise the rubeosis iridis. To detect and rec-ognize the rubeosis iridis, it needs to extract the detail of the image of iris using image processing methods. In this paper, the proposed method is to detect and recognize the rubeosis iridis by using the feature extraction and the datasets used for this project is Warsaw Biobase. Finally, the rubeosis iridis is detected and the proposed method is discussed on this paper. The results obtained from the exper-iment show that the normal and abnormal iris image can be classified using orig-inal and small size of iris image. In this experiment, abnormal original are greater than 1200000 pixel while for small size are less than 35000 pixel. Normal origi-nal size which is less than 1200000 pixel and for small are less than 25000 pixel. By considering this result, the proposed method can be extended to the iris mon-itoring system.
format	Conference or Workshop Item
author	Rohana, Abdul Karim Nur Amira Adila, Abd Mobin Nurul Wahidah, Arshad Nor Farizan, Zakaria M. Zabri, Abu Bakar
author_facet	Rohana, Abdul Karim Nur Amira Adila, Abd Mobin Nurul Wahidah, Arshad Nor Farizan, Zakaria M. Zabri, Abu Bakar
author_sort	Rohana, Abdul Karim
title	Early rubeosis iridis detection using feature extraction process
title_short	Early rubeosis iridis detection using feature extraction process
title_full	Early rubeosis iridis detection using feature extraction process
title_fullStr	Early rubeosis iridis detection using feature extraction process
title_full_unstemmed	Early rubeosis iridis detection using feature extraction process
title_sort	early rubeosis iridis detection using feature extraction process
publisher	Universiti Malaysia Pahang
publishDate	2019
url	http://umpir.ump.edu.my/id/eprint/26666/ http://umpir.ump.edu.my/id/eprint/26666/1/27.%20Early%20rubeosis%20iridis%20detection%20using%20feature%20extraction%20process.pdf http://umpir.ump.edu.my/id/eprint/26666/2/27.1%20Early%20rubeosis%20iridis%20detection%20using%20feature%20extraction%20process.pdf
first_indexed	2023-09-18T22:41:39Z
last_indexed	2023-09-18T22:41:39Z
_version_	1777416954938654720

Early rubeosis iridis detection using feature extraction process

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