Automatic extraction of blood vessels and veins using adaptive filters in Fundus image

Abstract

The paper proposes a novel method for extraction of blood vessels and veins from medical image of human eye - retinal fundus images that can be used in ophthalmology for detecting various eyes' diseases such glaucoma, diabetic retinopathy or macula oedema. The method utilizes an approach of preprocessing of image by using adaptive histogram equalization by CLAHE algorithm of green channel of fundus retinal image. Subsequently, using adaptive filters and image convolution with filter mask as key point of proposed algorithm and subsequently is applied the operation erosion processed image and removed small segments from image to enhance extraction of blood vessels from fundus image. The proposed technique analyzes detection and evaluates precision of the method on dataset from public fundus image libraries DRIVE, and HRF and compare with reference training results provided by these libraries..