Indian Journal of Science and Technology
Year: 2019, Volume: 12, Issue: 27, Pages: 1-8
V. R. Balaji* and J. Sathiya Priya
*Author for correspondence
V. R. Balaji
Department of Electronics and Communication Engineering, Sri Krishna College of Engineering and Technology, Coimbatore – 641008, Tamil Nadu, India; [email protected]
Objectives: To make the automatic detection of Glaucoma at early stage of the disease. Methods/Statistical Analysis: Fundoscopy is one of the medical specialty techniques to understand the inner structure of the membrane. In this study, we tend to project the combination of structural and textural characteristics of a fundus image to solidify the eye disease diagnosis. Findings: The planned technique introduces an extraction of structural and textural features by the Naive Bayes algorithm and it is classified using the decision tree algorithm to detect the glaucoma cases. Naive Bayes can be implemented fast and ease in the less dataset. The planned technique introduces a category of perpetrators in the machinecontrolled diagnosis in the event of any conflict in the determination of structural features. Application/Improvements: The estimate of the proposed algorithm is carried out using the local database of 100 patients with fundus images. It calculates the instance value to identify the glaucoma level. The proposed system gives exceptional results with better accuracy.
Keywords: Decision Tree, Fundus Images, Naive Bayes, PCA
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