Automatic Classification of Hypertensive Retinopathy by Gray Wolf Optimization Algorithm and Naïve Bayes Classification

Retinal blood vessels are affected by a variety of eye diseases, including hypertensive retinopathy (HR) and diabetic (DR). A person with HR needs to be sure check their eyes regularly, which requires the use computer vision methods analyze images back help ophthalmologists automatically. Automated diagnostic systems useful for diagnosing different retinal diseases patients who need establish an automated detection classification system using images. In this work, sliding band filter was used improve back-of-the-eye small convex regions develop detecting classifying gravity levels. An image improved wolf optimization along Bayes algorithm conducted. The current model tested publicly available dataset, its results were compared existing models. mentioned that model-improved Naïve classified severity levels on optimized features produced maximum accuracy 100% while being other classifiers.