Exudates segmentation using inverse surface adaptive thresholding

This paper presents a new approach to detect exudates and optic disc from color fundus images based on inverse surface thresholding. The strategy involves the applications of fuzzy c-means clustering, edge detection, otsu thresholding and inverse surface thresholding. The main advantage of the prop...

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Main Authors: Yazid, Haniza, Arof, Hamzah, Mohd Isa, Hazlita
Format: Article
Language:English
Published: Elsevier 2012
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Online Access:http://eprints.um.edu.my/10291/1/Exudates_segmentation_using_inverse_surface_adaptive_thresholding.pdf
http://eprints.um.edu.my/10291/
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spelling my.um.eprints.102912018-10-11T04:06:07Z http://eprints.um.edu.my/10291/ Exudates segmentation using inverse surface adaptive thresholding Yazid, Haniza Arof, Hamzah Mohd Isa, Hazlita TA Engineering (General). Civil engineering (General) This paper presents a new approach to detect exudates and optic disc from color fundus images based on inverse surface thresholding. The strategy involves the applications of fuzzy c-means clustering, edge detection, otsu thresholding and inverse surface thresholding. The main advantage of the proposed approach is that it does not depend on manually selected parameters that are normally chosen to suit the tested databases. When applied to two sets of databases the proposed method outperforms methods based on watershed segmentation and morphological reconstruction. The proposed method obtained 98.2 and 90.4 in terms of sensitivity for Standard Diabetic Retinopathy Database – Calibration Level 1 (DIARETDB1) and a local dataset provided by National University Hospital of Malaysia(NUHM), respectively. Elsevier 2012 Article PeerReviewed application/pdf en http://eprints.um.edu.my/10291/1/Exudates_segmentation_using_inverse_surface_adaptive_thresholding.pdf Yazid, Haniza and Arof, Hamzah and Mohd Isa, Hazlita (2012) Exudates segmentation using inverse surface adaptive thresholding. Measurement, 45. pp. 1599-1608. ISSN 0263-2241
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
language English
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Yazid, Haniza
Arof, Hamzah
Mohd Isa, Hazlita
Exudates segmentation using inverse surface adaptive thresholding
description This paper presents a new approach to detect exudates and optic disc from color fundus images based on inverse surface thresholding. The strategy involves the applications of fuzzy c-means clustering, edge detection, otsu thresholding and inverse surface thresholding. The main advantage of the proposed approach is that it does not depend on manually selected parameters that are normally chosen to suit the tested databases. When applied to two sets of databases the proposed method outperforms methods based on watershed segmentation and morphological reconstruction. The proposed method obtained 98.2 and 90.4 in terms of sensitivity for Standard Diabetic Retinopathy Database – Calibration Level 1 (DIARETDB1) and a local dataset provided by National University Hospital of Malaysia(NUHM), respectively.
format Article
author Yazid, Haniza
Arof, Hamzah
Mohd Isa, Hazlita
author_facet Yazid, Haniza
Arof, Hamzah
Mohd Isa, Hazlita
author_sort Yazid, Haniza
title Exudates segmentation using inverse surface adaptive thresholding
title_short Exudates segmentation using inverse surface adaptive thresholding
title_full Exudates segmentation using inverse surface adaptive thresholding
title_fullStr Exudates segmentation using inverse surface adaptive thresholding
title_full_unstemmed Exudates segmentation using inverse surface adaptive thresholding
title_sort exudates segmentation using inverse surface adaptive thresholding
publisher Elsevier
publishDate 2012
url http://eprints.um.edu.my/10291/1/Exudates_segmentation_using_inverse_surface_adaptive_thresholding.pdf
http://eprints.um.edu.my/10291/
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score 13.160551