Optic Disc Identification Methods for Retinal Images

Presented are the methods proposed by authors to identify and model the optic disc in colour retinal images. The first three our approaches localized the optic disc in two steps: a) in the green component of RGB image the optic disc area is detected based on texture indicators and pixel intensity...

Full description

Bibliographic Details
Main Authors: Florin Rotaru, Silviu Ioan Bejinariu, Cristina Diana Nita, Ramona Luca, Camelia Lazar
Format: Article
Language:English
Published: Institute of Mathematics and Computer Science of the Academy of Sciences of Moldova 2014-07-01
Series:Computer Science Journal of Moldova
Subjects:
Online Access:http://www.math.md/files/csjm/v22-n2/v22-n2-(pp186-210).pdf
id doaj-364aa62ef0724461bfab892d4b335ca5
record_format Article
spelling doaj-364aa62ef0724461bfab892d4b335ca52020-11-25T00:40:36ZengInstitute of Mathematics and Computer Science of the Academy of Sciences of MoldovaComputer Science Journal of Moldova1561-40422014-07-01222(65)186210Optic Disc Identification Methods for Retinal ImagesFlorin Rotaru0Silviu Ioan Bejinariu1Cristina Diana Nita2Ramona Luca3Camelia Lazar4Institute of Computer Science, Romanian Academy, Iasi Branch, RomaniaInstitute of Computer Science, Romanian Academy, Iasi Branch, RomaniaInstitute of Computer Science, Romanian Academy, Iasi Branch, RomaniaInstitute of Computer Science, Romanian Academy, Iasi Branch, RomaniaInstitute of Computer Science, Romanian Academy, Iasi Branch, RomaniaPresented are the methods proposed by authors to identify and model the optic disc in colour retinal images. The first three our approaches localized the optic disc in two steps: a) in the green component of RGB image the optic disc area is detected based on texture indicators and pixel intensity variance analysis; b) on the segmented area the optic disc edges are extracted and the resulted boundary is approximated by a Hough transform. The last implemented method identifies the optic disc area by analysis of blood vessels network extracted in the green channel of the original image. In the segmented area the optic disc edges are obtained by an iterative Canny algorithm and are approximated by a circle Hough transform. http://www.math.md/files/csjm/v22-n2/v22-n2-(pp186-210).pdfoptic discretinal imagesvessel segmentationHough transform
collection DOAJ
language English
format Article
sources DOAJ
author Florin Rotaru
Silviu Ioan Bejinariu
Cristina Diana Nita
Ramona Luca
Camelia Lazar
spellingShingle Florin Rotaru
Silviu Ioan Bejinariu
Cristina Diana Nita
Ramona Luca
Camelia Lazar
Optic Disc Identification Methods for Retinal Images
Computer Science Journal of Moldova
optic disc
retinal images
vessel segmentation
Hough transform
author_facet Florin Rotaru
Silviu Ioan Bejinariu
Cristina Diana Nita
Ramona Luca
Camelia Lazar
author_sort Florin Rotaru
title Optic Disc Identification Methods for Retinal Images
title_short Optic Disc Identification Methods for Retinal Images
title_full Optic Disc Identification Methods for Retinal Images
title_fullStr Optic Disc Identification Methods for Retinal Images
title_full_unstemmed Optic Disc Identification Methods for Retinal Images
title_sort optic disc identification methods for retinal images
publisher Institute of Mathematics and Computer Science of the Academy of Sciences of Moldova
series Computer Science Journal of Moldova
issn 1561-4042
publishDate 2014-07-01
description Presented are the methods proposed by authors to identify and model the optic disc in colour retinal images. The first three our approaches localized the optic disc in two steps: a) in the green component of RGB image the optic disc area is detected based on texture indicators and pixel intensity variance analysis; b) on the segmented area the optic disc edges are extracted and the resulted boundary is approximated by a Hough transform. The last implemented method identifies the optic disc area by analysis of blood vessels network extracted in the green channel of the original image. In the segmented area the optic disc edges are obtained by an iterative Canny algorithm and are approximated by a circle Hough transform.
topic optic disc
retinal images
vessel segmentation
Hough transform
url http://www.math.md/files/csjm/v22-n2/v22-n2-(pp186-210).pdf
work_keys_str_mv AT florinrotaru opticdiscidentificationmethodsforretinalimages
AT silviuioanbejinariu opticdiscidentificationmethodsforretinalimages
AT cristinadiananita opticdiscidentificationmethodsforretinalimages
AT ramonaluca opticdiscidentificationmethodsforretinalimages
AT camelialazar opticdiscidentificationmethodsforretinalimages
_version_ 1725289129513582592