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Abstract
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Article Information:
Glaucoma Detection From Fundus Image Using Opencv
K. Narasimhan, K. Vijayarekha, K.A. JogiNarayana, P. SivaPrasad and V. SatishKumar
Corresponding Author: K. Narasimhan
Submitted: March 18, 2012
Accepted: April 14, 2012
Published: December 15, 2012 |
Abstract:
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This study proposes a semi automated method for glaucoma detection using CDR and ISNT ratio
of a fundus image. CDR (Cup to Disc Ratio) is ratio of area of Optic Cup to area of Optic Disc. For a patient
with glaucoma Optic Cup size increases while the Optic Disc size remains same and hence CDR will be high
for glaucoma patient than normal fundus image. The ROI of green plane is taken and K-Means clustering
technique is recursively applied and Optic Disc and Optic Cup is segmented. Through elliptic fiiting, area of
Optic Disc and Cup is determined and hence CDR is calculated. ISNT is another parameter used for the
diagnosis of glaucoma which is determined through the ratio of area of blood vessels in Inferior Superior to
Nasal Temporal side. Blood vessels will shift to Nasal side for glaucoma patients, hence value will be less for
glaucoma patient than normal fundus image. Matched filter and Local entropy thresholding is applied to extract
blood vessels. The code is programmed in C++ using OpenCV library functions. OpenCV (Open Source
Computer Vision Library) is a library of programming functions developed by Intel. Core, highgui, imgproc,
ml are the main libraries used from OpenCV. The optimized functions in OpenCV increase the speed of
operation and is very much suitable for real time mass screening purpose. A batch of 50 retinal images (25
normal set and 25 abnormal set) obtained from the Aravind Eye Hospital, is used to assess the performance of
the proposed system.
Key words: Cup to Disk Ratio (CDR), fundusimage, Inferior Superior Nasal and Temporal (ISNT), K-means clustering, open CV , thresholding,
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Cite this Reference:
K. Narasimhan, K. Vijayarekha, K.A. JogiNarayana, P. SivaPrasad and V. SatishKumar, . Glaucoma Detection From Fundus Image Using Opencv. Research Journal of Applied Sciences, Engineering and Technology, (24): 5459-5463.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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