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Development of Digital Image Processing using Fuzzy Gaussian Filter Tool for Diagnosis of Eye Infection

by Jyoti Patil, A. L. Chaudhari
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 51 - Number 19
Year of Publication: 2012
Authors: Jyoti Patil, A. L. Chaudhari
10.5120/8149-1756

Jyoti Patil, A. L. Chaudhari . Development of Digital Image Processing using Fuzzy Gaussian Filter Tool for Diagnosis of Eye Infection. International Journal of Computer Applications. 51, 19 ( August 2012), 10-12. DOI=10.5120/8149-1756

@article{ 10.5120/8149-1756,
author = { Jyoti Patil, A. L. Chaudhari },
title = { Development of Digital Image Processing using Fuzzy Gaussian Filter Tool for Diagnosis of Eye Infection },
journal = { International Journal of Computer Applications },
issue_date = { August 2012 },
volume = { 51 },
number = { 19 },
month = { August },
year = { 2012 },
issn = { 0975-8887 },
pages = { 10-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume51/number19/8149-1756/ },
doi = { 10.5120/8149-1756 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:50:47.403073+05:30
%A Jyoti Patil
%A A. L. Chaudhari
%T Development of Digital Image Processing using Fuzzy Gaussian Filter Tool for Diagnosis of Eye Infection
%J International Journal of Computer Applications
%@ 0975-8887
%V 51
%N 19
%P 10-12
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Diabetic retinopathy eye disease which is harmful, cuases pressure in eye nerve fiber. Therefore it is essential to diagnose it earlier. In this paper we have process on images of retina with the help of Digital Image Processing (DIP) tool. In which images are getting detected and then processed. We distinguish the problem of detecting edges in images as a fuzzy logic problem. The edge detection problem can be separated into three stages: filtering, detection, and tracing. Images separated with the application of fuzzy reasoning based on local pixel characteristics which can control the degree of Gaussian smoothing. Filtered images are then applied to a simple edge detection algorithm which evaluates the edge fuzzy association value for each pixel, based on local image characteristics [1].

References
  1. Bill Silver, "An Introduction to Digital Image Processing", Cognex Corporation, Modular Vision SystemsDivision,2000.
  2. "computer assisted eye fungal infection diagnosis", A Thesis Submitted to the Graduate Faculty of the Louisiana State University and Agriculture and Mechanical College in partial fulfillment of the requirements for the degree of Master of Science in Systems Science
  3. M. Hanmandlu, Rohan Raj Kalra, Vamsi Krishna Madasu,Shantaram Vasikarla. "Area based Novel Approach for Fuzzy Edge Detection". Department of Electrical Engineering, Indian Institute of Technology, Delhi.
  4. Ma, L. , Tan, T. , Wang, Y. , Zhang, D. : "Personal Recognition Based on Iris Texture Analysis", IEEE Trans. Pattern Analysis and Machine Intelligence,25(12) (2003) 1519- 1533.
  5. Renyan Zhang, Guoling Zhao, Li Su. "New edge detection method in image processing". College of Autom. , Harbin Engineering University, China.
  6. Big Fang,Wynne, HsuMong Li Lee'" On the Detection of Retinal Vessels in Fundus Images" , Singapore-MIT Alliance , National University of Singapore, Department of Computer Science, School of Computing National University of Singapore.
  7. Iqbal, M. I , Aibinu, A. M ,Gubbal, N. S. Khan,"Automatic diagnosis of diabetic retinopathy using fundus images", Master's thesis Blekinge Institute of Technology October 2006
  8. Jing Wan, Xiaofu He, Pengfei Shi ," An Iris Image Quality Assessment Method Based on Laplacian of Gaussian Operation", Institute of Image Processing and Pattern Recognition, MVA2007 IAPR Conference on Machine
Index Terms

Computer Science
Information Sciences

Keywords

Diabetic Retinopathy Digital Image Processing MATLAB Fuzzy Gaussian Filter

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