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In this paper we show an optic disk (OD) detection approach based on evolution strategy (ES). The approach has two main steps: Coarse detection and contour edges refinement. Coarse detection estimates an approximated position using a ES in which each individual has a fitness function based on the bright pixels amount and the vasculature structure edge pixels quantity inside a circle. The contour edge refinement uses a geometrical approach to circle deformation in order to adjust the edge circle with OD edges. For this, the pixel with the largest intensity value variation along a normal line is considered. The proposed approach was evaluated using the STARED and DIAREDB public repository, processing normal and disease patient states retinal images. The results show that the proposed method identifies the optic disk position with an accuracy of 96 %. [ABSTRACT FROM AUTHOR]

Diabetic diseases affect the internal structures of the retina circulatory system. Diabetic retinopathy is considered the leading cause of blindness in adult populations; this aspect has motivated the development of several works related to the inclusion of computational techniques for analysis of retinal images. In this paper, we review and describe recent literature regarding digital retinal processing, particularly the automation of detection, segmentation and location of pathology processes, arising from diabetic retinopathy condition. A pathology type-based classification was performed. [ABSTRACT FROM AUTHOR]