Transactions of the SDPS: Journal of Integrated Design and Process Science 20 (1), 2016, 65-76 DOI 10.3233/jid-2016-0003 http://www.sdpsnet.org 1092-0617/€27.50© 2016- Society for Design and Process Science. All rights reserved. Published by IOS Press Automatic Cotton Wool Spots Extraction in Retinal Images Using Texture Segmentation and Gabor Wavelet Bushra Shabbir a , Muhammad Sharif a , Wasif Nisar a , Mussarat Yasmin a* , Steven Lawrence Fernandes b a Department of Computer Science, COMSATS Institute of Information Technology, Wah Cantt, Pakistan b Department of Electronics and Communication Engineering, Sahyadri College of Engineering & Management, Mangalore, Karnataka, India Abstract Hypertensive Retinopathy is a very serious disease that harms the retina of eye and is mainly caused by severe hypertension. A major sign of Hypertensive Retinopathy is Cotton Wool Spots which can lead to visual loss. Hypertensive patient can be saved from ocular complications, stroke and heart attacks by early detection of these spots. An efficient automated method for cotton wool spots detection is presented in this paper. Three major stages are involved in the proposed algorithm namely; pre-processing, segmentation and feature extraction. There are many techniques of pre-processing noisy fundus images that can be applied for noise removal and features enhancement in order to equalize regions having uneven contrast. Optic disc in retinal image has cotton wool spots characteristics like contrast, colour and intensity. The automatic detection of cotton wool spots gets confused during automated evaluation. Because of this reason, in image segmentation stage, optic disc is eliminated earlier by using Texture Segmentation and Gabor Wavelet. Finally in feature extraction, cotton wool spots are detected using Otsu thresholding method. According to the experiments which are conducted on the basis of pixels, the proposed algorithm achieves better results. Keywords: Cotton wool spots, optic disc, Texture Segmentation, Hypertensive Retinopathy, Gabor Wavelets 1. Introduction High blood pressure is a major cause of retinal disorder called Hypertensive Retinopathy (HR). Hypertension affects nearly one billion people worldwide and approximately 50 million people in United States every year. Long duration and severe hypertension increase the incidence of retinopathy (Erden & Bicakci, 2012; Zamir et al., 1979). Because of the increasing number of HR patients, it has become a threat for the society. HR can damage the blood vessels of retina (Abràmoff et al., 2010; Wong et al., 2001). It is characterized in different people by different vascular signs of retina with preeminent blood pressure. Ophthalmoscope usage for HR detection has been considered as a part of standard assessment (Wong, et al., 2001). In screening programs for HR prevention, digital colour fundus image is an easiest method for eye fundus analysis. However, because of the growing number of patients with HR, a large number of images must be examined by ophthalmologists. Therefore, developing computational tools is * Corresponding author. Email: mussaratyasmin@comsats.edu.pk