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Reseach Article

Retinal Blood Vessels Extraction using Matched Filter on High Resolution Fundus Image Database

Published on April 2015 by Deepali D. Rathod, Ramesh R. Manza, Yogesh M. Rajput
National conference on Digital Image and Signal Processing
Foundation of Computer Science USA
DISP2015 - Number 1
April 2015
Authors: Deepali D. Rathod, Ramesh R. Manza, Yogesh M. Rajput
bb0a8204-fd64-4dec-a8bb-c5bb62e6702b

Deepali D. Rathod, Ramesh R. Manza, Yogesh M. Rajput . Retinal Blood Vessels Extraction using Matched Filter on High Resolution Fundus Image Database. National conference on Digital Image and Signal Processing. DISP2015, 1 (April 2015), 15-22.

@article{
author = { Deepali D. Rathod, Ramesh R. Manza, Yogesh M. Rajput },
title = { Retinal Blood Vessels Extraction using Matched Filter on High Resolution Fundus Image Database },
journal = { National conference on Digital Image and Signal Processing },
issue_date = { April 2015 },
volume = { DISP2015 },
number = { 1 },
month = { April },
year = { 2015 },
issn = 0975-8887,
pages = { 15-22 },
numpages = 8,
url = { /proceedings/disp2015/number1/20478-3005/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National conference on Digital Image and Signal Processing
%A Deepali D. Rathod
%A Ramesh R. Manza
%A Yogesh M. Rajput
%T Retinal Blood Vessels Extraction using Matched Filter on High Resolution Fundus Image Database
%J National conference on Digital Image and Signal Processing
%@ 0975-8887
%V DISP2015
%N 1
%P 15-22
%D 2015
%I International Journal of Computer Applications
Abstract

In this paper we have extracted the retinal blood vessels using 2D Matched filter. The proposed algorithm is consisting of some preprocessing steps on RGB image like extraction of green channel; contrast limited adaptive histogram equalization, and morphological opening operation. After extraction of retinal blood vessels using matched filter, we have calculated fractal dimension for finding the architectural distortion. Accuracy is calculated using person correlation coefficient, and achieved 98. 3 % accuracy. Operations are done on the 45 images of HRF database. 15 images are of Healthy, 15 images are of Diabetic retinopathy, and 15 are of Glaucoma.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Diabetic Retinopathy Retinal Blood Vessels Matched Filter Hrf Database