Intelligent Detection of Foveal Zone from Colored Fundus Images of Human Retina Through a Robust Combination of Fuzzy-Logic and Active Contour Model

Detection of the center of a fovea and its boundary from a retinal image is a challenging task due to the irregularity of the avascular foveal region. Several attempts have been made before in order to detect the foveal region and its boundary from fluorescein angiographic images. The irregularity and large variation in the human retinal images made the task increasingly difficult. In this current work funds images were considered instead of fluorescein angiographic images in order to ensure the applicability of the proposed algorithm in both biomedical and biometric analysis. A robust fuzzy-rule based image segmentation algorithm has been developed in order to extract the foveal region from a wide variety of images from different persons. Detection of foveal region comprised of locating the geometric center and extracting the boundary. The geometric center was evaluated by weighted averaging the grey scale intensities obtained from implementing the current algorithm. This was followed by applying gradient vector flow (GVF) based active contour technique in order to extract the boundary of the foveal region. The algorithm was applied on a several retinal images acquired from different persons with a very good success rate. The present work is considered to be an important contribution in intelligent image analysis of human retina since it incorporates a robust “fuzzy-rule” in extracting foveal region. Similar approach has not been adopted in the literature. The proposed algorithm is seen to be versatile in analyzing a wide range of retinal images.