Comparison between empirical and variational mode decomposition based on percentage variation in entropy feature from glaucoma image Kirar Bhupendra Singh1,*, Agrawal Dheeraj Kumar2 1Ph. D. Research Scholar Department of Electronics and Communication Engineering, Maulana Azad National Institute of Technology, Bhopal, India 2Assistant Professor, Department of Electronics and Communication Engineering, Maulana Azad National Institute of Technology, Bhopal, India *Corresponding Author: Bhupendra Singh Kirar Ph. D. Research Scholar, Department of Electronics and Communication Engineering, Maulana Azad National Institute of Technology, Bhopal, India Email: bhup17@gmail.com
Online published on 25 September, 2018. Abstract Glaucoma is a type of eye disease; it damages the optic nerve due to gradual increase in the fluid pressure and hence causes blindness. In the paper two decomposition techniques, namely, bi-dimensional empirical mode decomposition (BDEMD) and two dimensional variational mode decomposition (2DvMD) are used and compared to find the better decomposition technique. Images are decomposed by these methods and entropy features are extracted from decomposed sub band images. The percentage variations in entropy features have been calculated from the extracted features for each decomposition technique for normal and glaucoma image. These calculated percentage variations in entropy features are used to compare the two decomposition techniques for normal and glaucoma images. The results obtained put forward that the percentage variation in entropy feature extracted from 2DvMD are higher than BDEMD. Hence, 2DvMD outperforms over BDEMD. Top Keywords Glaucoma, BDEMD, 2DVMD, Entropy, PVEF. Top |