Retinal Blood Vessel Segmentation using Ant Colony System
D. Ratnagiri1, G. Murali2

1D. Ratnagiri, Research Scholar, Department of Computer Science and Engineering, Acharya Nagarjuna University, Nagarjuna Nagar, Guntur District, Andhra Pradesh, India.

2G. Murali, Professor, Department of Computer Science and Engineering, KKR and KSR Institute of Technology and Sciences, Guntur District, Andhra Pradesh, India.

Manuscript received on 7 June 2019 | Revised Manuscript received on 12 June 2019 | Manuscript Published on 08 July 2019 | PP: 10-14 | Volume-8 Issue-8S3 June 2019 | Retrieval Number: H10050688S319/19©BEIESP

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Abstract: Diabetic retinopathy infection spreading on the retina vessels along these lines and it loses blood circulation that causes the visual loss in the time, so early identification of diabetes anticipates visual impairment in over half of cases. The programmed division of corneal veins into two-grade corneal images could achieve early representation. In this paper, the ant-colony technique for programmed dividing retinal arteries is used in two improvements in the previous methodology. Finally, the second development is the application of special heuristic capabilities in the ant-colony method, completely dependent on the supposition of chance, rather than the old one recently used on Euclidean distance. In our own database is for everyone a solitary database, which has a very pathology for diabetes retinopathy and important fundus structures, which is still clarified for each image in a database that makes it attractive for planning and assessing estimations of the diabetic retinopathy by coloring fundus images, which are currently reachable and completely new for early identification.

Keywords: Diabetic retinopathy, Morphological process, SVM, Digital Image Processing, Machine learning
Scope of the Article: Machine Learning