Detection of Blood Vessels in Retina Images using Gray Level Grouping Method

The most important part of the eye is the retina that covers the entire back part of the eye. eye diseases are one of the most important causes of disability and even death in developed countries as well as in developing countries. disorders created in the retina that occur due to special diseases can be detected by specific retinal images. studying the changes in retinal images in a specific time period can help physicians to diagnose the related diseases. in the present paper, the detection of blood vessels in retina images has been investigated. for this purpose, first a new method is proposed to improve the quality of retina images by combining the histogram adjustment and gray level grouping. we use the feature vector to classify the pixels. next, a method for classifying the images based on the feature extraction vector is required. the use of neural networks is one of the best and most widely used methods of machine learning for classification. we used a 3-layer perceptron to classify pixels.