Detection of anatomical features in retinal images using a gradient orientation

A computer-assisted system for diagnosis of eye diseases has been in great demand. This paper presents a robust and efficient method for the detection of anatomical features in retinal images. The method is based on the analysis of gradient orientation and is not directly affected by image intensity. For this, the method performs very well in spite of the inherent problems of the retinal images, such as low contrast and non-uniform illumination. The method can detect features with circular and liner structures efficiently. A multi-scale approach is employed to detect various sizes of features, especially blood vessels with varying diameters. The extraction of the blood vessel network from the detected features is also described.