Feature Selection for Simple Color Histogram Filter based on Retinal Fundus Images for Diabetic Retinopathy Recognition

Abstract

Applications of learning models for text-based datasets as well as image pixels-based datasets grow rapidly for prediction purposes. Pre-processing becomes challenging in carrying out image filtering and classifying. Retinal Fundus images plays important role in Diabetic Retinopathy (DR) diagnosis and treatment planning in various stages. Diabetic Retinopathy is diagnosed by observing the variation in retinal blood vessel, exudates, micro aneurysm, hemorrhages, and the new blood vessel growth inside the retina. The objective of this study is to enrich the diagnosis for the Diabetic Retinopathy from the retinal fundus images by applying machine learning algorithms. The proposed work implements normalization, parameter tuning, and optimal feature selection method to improve the classification accuracy offered by selected algorithms like decision tree algorithm and K-nearest neighborhood classifiers. The highest accuracy of 81.99%, Weighted Average of Receiver Operating Characteristics (ROC) 0.907 are obtained by k-Nearest Neighbor (KNN) classifier due to its best performance.

KEYWORDS:

• Attribute selection
• Diabetic Retinopathy
• J48
• KNN
• Simple color histogram filter
• WEKA

Additional information

Notes on contributors

T. Vijayan

T Vijayan is working as a assistant professor and part time research scholar, Department of Electronics and Communication Engineering, Bharath Institute of Higher Education and Research, Chennai. He received his ME degree in communication system from Anna University, Chennai, in 2010. He received the BE degree in electronics and communication engineering from Anna University, Chennai, in 2008. His current research interests include artificial intelligence, machine learning, soft computing, digital image processing, signal processing and communication systems.

M. Sangeetha

M Sangeetha received the BE degree from the Bharathidasan University, in 1996, the ME degree from the University of Madras, in 1999 and the PhD degree in electronics and communication engineering from Anna University in 2010. She is presently professor of electronics and communication engineering, Bharath Institute of Higher Education and Research. She is also a member of IET and ISTE. Email: [email protected]

A. Kumaravel

A Kumaravel is working as a professor and dean, School of Computing, Bharath Institute of Higher Education and Research, Chennai. His research interest includes functional paradigm, soft computing, cloud computing, machine learning, computational intelligence, and knowledge engineering. He is a life Member of ISTE and IET. He is a reviewer for IEEE Transactions and Elsevier journals. Email: [email protected]

B. Karthik

B Karthik is an associate professor in the Department of Electronics and Communication Engineering, Bharath Institute of Higher Education and Research, Chennai, India. He received his PhD (ECE) – Image Processing in May 2017. He received his Master of Engineering – Applied Electronics at Thiruvalluvar College of Engineering & Technology in 2011. He received his Bachelor of Technology in electronics and communication engineering at Bharath Institute of Higher Education and Research, Chennai, India in 2007. His research interests include image & video processing, cryptography and network security system techniques. He is a member of IEEE, ITEEA, IAIP, CSTA, and IAENG. Email: [email protected]