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A Hybrid Entropy Based Method Using Gaussian Kernel for Retinal Blood Vessel Segmentation

  • N. K. Adhish
  • R. RajeshEmail author
  • T. M. Thasleema
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 940)

Abstract

Extraction of blood vessel from the retina is a major task for detecting/diagnosing eye related diseases such as diabetes, glaucoma etc. Manual segmentation is a difficult task and can be made easier by developing automated segmentation algorithms. This paper presents a quick survey of retinal segmentation methods. An entropy based optimal thresholded and length filtered image obtained from the matched filter response of Gaussian probability distribution function kernel on the enhanced (by contrast limited adaptive histogram equalization) green channel image is proposed and it gives better result when compared to other works in the literature.

Keywords

Retinal blood vessels Segmentation Gaussian probability distribution function 

Notes

Acknowledgments

The authors would like to thank Central University of Kerala for providing support for carrying out this research work.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer ScienceCentral University of KeralaPeriyaIndia

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