Research Journal of Pharmacy and Technology
SCOPUS
  • Year: 2018
  • Volume: 11
  • Issue: 6

Detection and segmentation of retinal blood vessel in digital RGB and CIELUV color space fundus images

  • Author:
  • P Ganesan1,, L.M.I. Leo Joseph2, M. Ravichandran3, K.M. Subramanian3, S Anu Velavan4
  • Total Page Count: 5
  • Page Number: 2326 to 2330

1Department of Electronics and Communication Engineering, Vidya Jyothi Institute of Technology, Hyderabad

2Department of Electronics and Communication Engineering, S.R. Engineering College, Warangal, India

3Department of Computer Science and Engineering, Shadan College of Engineering, Hyderabad, India

4Department of Computer Science and Engineering, UCE-BIT Campus, Anna University, Tiruchirappalli, India

*Corresponding Author E-mail: gganeshnathan@gmail.com

Online published on 24 August, 2018.

Abstract

The identification of retinal blood vessels is very important but crucial task to analyze the severity of the retinal diseases such as diabetic retinopathy, macular degeneration, central retinal vein occlusion, central retinal artery occlusion, retinal detachment and branch retinal vein occlusion. It is evident that huge number of computer based automated algorithms are developed for the accurate detection of blood vessels and optical disc. Most of the work utilizes the retinal fundus images in RGB color space. The proposed work implements the detection and segmentation of retinal blood vessel in RGB and device independent CIELUV color space. The proposed work for the segmentation retinal blood vessel is based on adaptive histogram equalization, median filtering and morphological operations.

Keywords

Segmentation, Retinal Blood Vessel, Adaptive Histogram Equalization, Median Filtering, Mathematical Morphology