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Identifying Abnormalities in the Retinal Images using SVM Classifiers
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 111 - Number 6 |
| Year of Publication: 2015 |
| Authors: Shantala Giraddi, Jagadeesh Pujari, Shivanand Seeri |
10.5120/19540-9686
|
Shantala Giraddi, Jagadeesh Pujari, Shivanand Seeri . Identifying Abnormalities in the Retinal Images using SVM Classifiers. International Journal of Computer Applications. 111, 6 ( February 2015), 5-8. DOI=10.5120/19540-9686
Abstract
Automated early detection of exudates in retinal images is a challenging task. With the global diabetic population increasing at an alarming rate, there is need for development of automated systems for detection of exudates. The main obstacle in exudates detection is extreme variability of color and contrast in retinal images that depends on the degree of pigmentation, size of the pupil and illumination. The aim of this paper is to develop and validate systems for detection of hard exudates and classify the input image as normal or diseased one. The authors have proposed and implemented novel method based on color and texture features. Performance analysis of SVM and KNN classifiers is presented. Images classified by these classifiers are validated by expert opthamalagists.
References
- Abha Gupta Caroline Styles Brtitish Journal Of Diabetes and Vascular Disease doi: 0. 1177/1474651410374192 British Journal of Diabetes & Vascular Disease September/October 2010 vol. 10 no. 5 224-230
- Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care 2004; 27: 1047
- http://www. mayoclinic. org/diseases- conditions/diabetic- retinopathy/basics//symptoms/con-20023311 20023311
- C. I. Sanchez Roberto Hornero , Mar´?a I. L´opez , Mateo Aboy ,Jes´us Poza , Daniel Ab´asolo " A Novel automatic image processing algorithm for detection of hard exudates based on retinal image analysis" ,Medical Engineering and Physics , pp 350-357, Issue 30 2008.
- Shantala Giraddi, Dr Jagadeesh Pujari, "Role of GLCM features in Identifying Abnormalities in the Retinal Images", Accepted IJGSP To be published
- H. F. Jaafar, A. K. Nandi and W. Al-Nauimy, "Automated detection of exudates in retinal images using a split-and-merge algorithm," EUSIPCO 2010, Alborg, pp. 1622-1626, 2010.
- Nidhal K. El Abbadi Enas Hamood Al- Saadi , "Automatic Detection of Exudates in Retinal Images", International Journal of Computer Science Issues, Vol. 10, Issue 2, No 1, March 2013
- H. F. Jaafar, A. K. Nandi and W. Al-Nauimy, "Automated detection of exudates in retinal images using a split-and-merge algorithm," EUSIPCO 2010, Alborg, pp. 1622-1626, 2010.
- Nidhal K. El Abbadi Enas Hamood Al- Saadi , "Automatic Detection of Exudates in Retinal Images", International Journal of Computer Science Issues, Vol. 10, Issue 2, No 1, March 2013
- Xiwei Zhanga, , , Guillaume Thibaulta, Etienne Decencièrea, , Beatriz Marcoteguia, Bruno Laÿd, Ronan Dannod, Guy Cazuguele, f, Gwénolé Quellecf, Mathieu Lamarde, f, Pascale Massinb,
- Agnès Chabouisc, Zeynep Victorb, Ali Erginayb "Exudate detection in color retinal images for mass screening of diabetic retinopathy" DOI: 10. 1016/j. media. 2014. 05. 004
- Juan Martin Cardenas, M. Elena Martinez-Perez ,Francesc March, Nidiyare Hevea-Montiel "Mean Shift Based Automatic Detection Of Exudates in retinal Images" Advances in Intelligent Systems and Computing Volume 184, 2013, pp 73-82.
- Gidudu Anthony, Hulley Gregg and Marwala Tshilidzi
- Image Classification Using SVMs: One-against-One Vs One-against-All, http://arxiv. org/ftp/arxiv/papers/0711/0711. 2914. pdf
- Fix, E. and HODGES, J. L. JR. (1951). Discriminatory Analysis, Nonparametric Discrimination: Consistency Properties. Report No. 4, Project No. 21-49-004, USAF School of Aviation Medicine.
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