A Methodology to Segment Retinal Vessels Using Region-Based Features

Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 10)

Abstract

Analysis of the retinal blood vessels has become remarkable area of research in biomedical field. This paper presents fundus image blood vessel segmentation approach using region-based features. In the pre-processing phase, the input fundus image is segmented as major vessel and minor vessel region. Further, to enhance segmentation accuracy region-based features are extracted from minor vessels by applying morphological operations. Fuzzy entropy measure is used to select the relevant features and for classification, a k-NN classifier is employed. The proposed algorithm is evaluated using two openly available data sets DRIVE and CHASE_DB1. The method presented is independent of training samples and achieves 96.75% of classification accuracy.

Keywords

Diabetic retinopathy Morphology Region based feature Fundus images Fuzzy entropy measure k-NN classifier 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Electronics & TelecommunicationPillai HOC College of Engineering & TechnologyRaigadIndia

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