Journal Press India^®

Author Details ( * ) denotes Corresponding author

Diabetic retinopathy (DR) is one of the pre-eminent causes of blindness among the diabetic affected patient. DR is caused by the sensitive tissue in the retina because of the damaged blood vessels. Early detection of DR can potentially reduce the risk of blindness and it could be prevented with an early screening process .In this paper authors have attempt to develop an automated exudates detection system for the classification of retinal image into exudates and non-exudates using PNN classifier. The methodologies involved in this work are Pre-processing, Optic disc elimination, Segmentation of exudates using K-means clustering technique, to classify these segmented images into exudates and non-Exudates image, a set of features based on texture and color are extracted using Gray Level Co-Occurrence Matrix (GLCM). Feature selection is done using Genetic Algorithm, and then these selected features are classified into exudates and non-exudates using Probabilistic Neural Network (PNN) classifier with an accuracy of 96.9%.

Keywords

Diabetic Retinopathy; Exudates; K-means; GLCM; Genetic Algorithm; PNN.

1. DIARETDB0 database, Available at: http://www.it.lut.fi/project/imageret/diaretdb0/


2. DIARETDB1 database, Available at: http://www.it.lut.fi/project/imageret/diaretdb1/


3. DRIVE database, Available at: http://www.isi.uu.nl/Research/Database/DRIVE/


4. STARE database, Available at: http://www.ces.clemson.edu/~ahoover/stare


5. G.S Annie Grace Vimala and S.Kaja mohideen, “An Efficient Approach for Detection of Exudates in Diabetic Retinopathy Images Using Clustering Algorithm”,IOSRJCE, vol. 2, pp. 43-48, issue 5 July-Aug 2012.


6. A.Elbalaoui, M.Fakir, A.Merbouha. Segmentation and Detection of Diabetic Retinopathy Exudates,International Journal of Computer Applications (0975 – 8887) Volume 91 – No.16, April 2014.


7. V. Ratna Bhargavi and V. Rajesh (2015) .Exudate Detection and Feature Extraction using Active contour Model and Sift in Color Fundus Images,ARPN Journal of Engineering and Applied Sciences,Volume 10, no. 6.


8. Asha gowda karegowda, Asfiya Nasiha, M.A.Jayaram and A.S.Manjunath, “Exudates detection in Retinal Images using Back Propagation Neural Network”, International Journal of Computer Applications(0975-8887), vol.25, No.3, pp.25-31, July 2011.


9. M. Ponni Bala, S. Vijayachitra, “computerised Retinal Image Analysis to detect and quantify Exudates Associated with Diabetic Retinopathy”, International Journal of Computer Applications(0975-8887), vol.54, No.2, September 2012.


10. Hussain F. Jaafar, Asoke K. Nandi and Waleed Al-Nuaimy, “Automated Detection and Grading of Hard Exudates from Retinal fundus images” 19th European Signal Processing Conference (EUSIPCO 2011), September 2, 2011.


11. D Gowrishankar, G Ramprabu, E Bharathi, R Divya, S Thulasi, “Automatic Extraction of Blood Vessels and Exudates Segmentation for Diabetic Retinopathy Detection”, International Journal of Innovative Research in Science, Engineering and technology, vol.4, Issue 3, March 2015.


12. Arti taneja, Dr. Priya Ranjan, Dr. Amit ujjlayan,” A performance Study of Image Segmentation Techniques”, IEEE, 2015.


13. Wawan Setiawan and Wiweka, “Combining of Image Classification With Probabilistic Neural Network (PNN) Approaches Based on Expectation Maximum (EM)”,IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 4, No 3, July 2012.


14. Asha Gowda Karegowda, Bharathi .P.T, M.A Jayaram, A.S.Manjunath, “ Automated detection of exudates in diabetic Retinopathy using Traditional and machine Learning Techniques: An overview”, International Conference on computing, New Delhi, Dec 2010.


15. Marzie Zahmatkesh, Ali Rafiee, Majid Mazinani, “Intelligent Diabetic Retinopathy diagnosis in retinal images”,Journal of Advances in Computer Research, (Vol. 4, 3, 2013,: 103-117.


16. R.Nithya , B.Santhi, “Mammogram classification using maximum difference feature selection method “,Journal of Theoretical and Applied Information Technology,30th November. 33 2. 2011


17. Babatunde Oluleye,Armstrong Leisa, Jinsong Leng, Diepeveen Dean,”A Genetic algorithm-Based Feature Selection”, International Journal of Electronics Communication and Computer Engineering, 5, 4.