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An Efficient Preprocessing Step for Retinal Vessel Segmentation via Optic Nerve Head Exclusion

  • Farha Fatina WahidEmail author
  • G. Raju
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1046)

Abstract

Retinal vessel segmentation plays a significant role for accurate diagnostics of ophthalmic diseases. In this paper, a novel preprocessing step for retinal vessel segmentation via optic nerve head exclusion is proposed. The idea relies in the fact that the exclusion of brighter optic nerve head prior to contrast enhancement process can better enhance the blood vessels for accurate segmentation. A histogram based intensity thresholding scheme is introduced in order to extract the optic nerve head which is then replaced by its surrounding background pixels. The efficacy of the proposed preprocessing step is established by segmenting the retinal vessels from the optic nerve head excluded image enhanced using CLAHE algorithm. Experimental works are carried out with fundus images from DRIVE database. It shows that 1%–3% of improvement in terms of TPR measure is achieved.

Keywords

Fundus image enhancement Retinal vessel segmentation Optic nerve head Preprocessing 

Notes

Acknowledgement

The authors would like to acknowledge the University Grants Commission (UGC), New Delhi, India for the financial support extended under Maulana Azad National Fellowship (MANF) scheme.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Information TechnologyKannur UniversityKannurIndia
  2. 2.Department of CSE, Faculty of EngineeringChrist (Deemed to be University)BengaluruIndia

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