Open AccessContent‐based retinal image retrieval
Author(s) -
Sukhia Komal Nain,
Riaz Muhammad Mohsin,
Ghafoor Abdul
Publication year - 2019
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2018.6371
Subject(s) - computer science , artificial intelligence , segmentation , image retrieval , computer vision , content based image retrieval , diabetic retinopathy , retina , retinal , image segmentation , image texture , pattern recognition (psychology) , image processing , image (mathematics) , ophthalmology , medicine , physics , optics , diabetes mellitus , endocrinology
The study presents a content‐based retrieval technique for retinal images. Given a query image, the aim is to automatically retrieve the relevant disease images (i.e. diabetic retinopathy, coats and choroidal neovascularisation) from the database. The proposed technique applies different pre‐processing steps to enhance the region of the exudate present in the retina. Segmentation step separates the exudates and vessels region to extract shape and texture features which are optimally combined with an automatic weight assignment approach. The simulations are performed on STARE dataset and compared with other existing techniques to ensure the significance of the proposed technique.