Ant Colony-based System for Retinal Blood Vessels Segmentation

  • Ahmed. H. Asad
  • Ahmad Taher Azar
  • Aboul Ella Hassaanien
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 201)


The segmentation of retinal blood vessels in the eye funds images is crucial stage in diagnosing infection of diabetic retinopathy. Traditionally, the vascular network is mapped by hand in a time-consuming process that requires both training and skill. Automating the process allows consistency, and most importantly, frees up the time that a skilled technician or doctor would normally use for manual screening. Several studies were carried out on the segmentation of blood vessels in general, however only a small number of them were associated to retinal blood vessels. In this paper, an approach for segmenting retinal blood vessels is presented using only ant colony system. It uses eight features; four are based on gray-level and four are based on Hu moment-invariants. The features are directly computed from values of image pixels, so they take about 90 s in computation. The performance evaluation of this system is estimated by using classification accuracy. The presented approach accuracy is 90.28 % and its sensitivity is 74 %.


Segmentation Retinal blood vessels Features extraction Ant colony system Moment-invariants Diabetic retinopathy 


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Copyright information

© Springer India 2013

Authors and Affiliations

  • Ahmed. H. Asad
    • 1
  • Ahmad Taher Azar
    • 2
  • Aboul Ella Hassaanien
    • 3
  1. 1.Institute of Statistical Studies and Researches, CS DepartmentCairo UniversityGizaEgypt
  2. 2.Misr University for Science and Technology (MUST), Scientific Research Group in Egypt (SRGE)6th of October CityEgypt
  3. 3.IT DepartmentCairo UniversityGizaEgypt

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