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Research Article

Year : 2019 | Volume: 5 | Issue: 2 | Pages: 1-6

Morphologic Adaptive Fuzzy Threshold Based Retinal Segmentation for Automatic Eye Screening

V Vincena1*, P Sherly Kanaga Priya2

https://dx.doi.org/doi:10.18831/djcse.in/12019021001

Corresponding author

V Vincena*

PG Scholar, Department of computer science and engineering, C.S.I. Institute of Technology, Thovalai, Tamil Nadu, India.

  • 1. PG Scholar, Department of computer science and engineering, C.S.I. Institute of Technology, Thovalai, Tamil Nadu, India.
  • 2. Assistant Professor, Department of Computer Science and Engineering, C.S.I. Institute of Technology, Thovalai, Tamil Nadu, India.

Received on: 2019/03/14

Revised on: 2019/04/29

Accepted on: 2019/04/08

Published on: 2019/04/15

  • Morphologic Adaptive Fuzzy Threshold Based Retinal Segmentation for Automatic Eye Screening , V Vincena, P Sherly Kanaga Priya, 2019/04/15, Journal of Excellence in Computer Science and Engineering, 5(2), 1-6, https://dx.doi.org/10.18831/djcse.in/12019021001.

    Published on: 2019/04/15

Abstract

Strength in similarity is considered to be a major task in terms of image segmentation particularly in segmenting retinal images. Rather than focussing on a solitary algorithm for the identification and extraction of multiple anatomical structures is treated as a challenging task during segmentation of retinal image because of the drastic variations their anatomical as well as non-anatomical retinal structure. An innovative, strong and stand-alone algorithm formed by the hybrid integration of adaptive fuzzy thresholding along with mathematical morphology is utilised for the extraction of multiple objects of anatomical nature consisting of extensive structures and features found in retinal images is proposed. For the purposes of solid analysis and overall clinical insight, the proposed work detects such anatomical structure in a single phase with an added advantage of high accuracy even in the case of compulsive images. Extraction of optic disk, exudate lesions as well as retinal vessels is carried out without analysing the texture. Moreover, the algorithm works better for the extraction of optic disc and vessels from compulsive images.

Keywords

Multiple anatomical structures, Adaptive fuzzy thresholding, Mathematical morphology, Retinal vessels, Optic disk, Exudate lesions.