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

  • Majid Eskandari Shahraki Master student, Faculty of Electrical Engineering , Islamic Azad University , Mobarakeh Branch , Mobarakeh, Isfahan, Iran
  • Mehran Emadi Assistant Professor, Faculty of Electrical Engineering,Islamic Azad University, Mobarakeh Branch, Mobarakeh, Isfahan, Iran
Keywords: Histogram modulation, Gray level grouping, Feature extraction vector, Perceptron neural network, Retinal images


The main part of the eye is the retina covering the entire back section of the eye. Eye disease is one of the most important cause 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 variations in retinal photos in a special time could help physicians to diagnose the associated diseases. In this paper, the detection of blood veins in retina photos was investigated. For this purpose, first a new method is proposed to promote the quality of retina photos 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.


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How to Cite
Eskandari Shahraki, M., & Emadi, M. (2020). Detection of Blood Vessels in Retina Images using Gray Level Grouping Method. Majlesi Journal of Telecommunication Devices, 9(1), 1-8. Retrieved from