Advances in Distributed Computing and Artificial Intelligence Journal (Jun 2020)

Detection of Hard Exudates in Retinopathy Images

  • Satya Bhushan VERMA,
  • Abhay Kumar YADAV

DOI
https://doi.org/10.14201/ADCAIJ2019844148
Journal volume & issue
Vol. 8, no. 4
pp. 41 – 48

Abstract

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The tissue layer located at the back of the eye is known as retina which converts the incoming light into nerve signals and those signals are sent to the brain for understanding. The damage onto the retina is termed as retinopathy and that may lead to vision weakening or vision loss. The hard exudates are small white or yellowish white deposits with their edges being clear and sharp. In the proposed methods we take color image of retina then extract the green channel of that image then apply top hat transformation and bottom hat transformation on that image. The DIARETDB1 and High-Resolution Fundus (HRF) databases are used for performance evaluation of the proposed method. The proposed technique achieves accuracy 97%, sensitivity 95%, and specificity 96% and it takes average 5.6135 second for detection of hard exudates in an image.

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