Glaucoma Detection Using Image Channels and Discrete Wavelet Transform

Abstract

Glaucoma is a critical retinal disorder due to high intraocular pressure (IOP) within the eye. It causes irreversible damage of the optical nerve head (ONH). The available glaucoma detection methods using decomposition techniques with gray images or only green channel images are less accurate. In this paper, a more accurate method for glaucoma detection using image channels (ICs) and discrete wavelet transform (DWT) from fundus images is proposed. Firstly, input images are resized then red channel (RC), green channel (GC), blue channel (BC), and gray scale (Gs) images are extracted. Secondly, these four types of images are enhanced and decomposed separately into sub band images (SBIs) using second level (SL) DWT. Thirdly, most useful features are extracted from each of DWT SBIs. Fourthly, extracted features from each of RC, GC, BC, and Gs images are concatenated and normalized. Finally, robust features are selected and fed to the least square support vector machine (LS-SVM) classifier. The obtained glaucoma detection accuracy of the proposed method is 84.95% which is more than the existing methods using the same image database. The proposed method may become suitable for ophthalmologists to detect glaucoma with better accuracy.

KEYWORDS:

• Discrete wavelet transform
• Features concatenation and normalization
• Features extraction
• Features selection and reduction
• Glaucoma
• Histogram equalization and filtering
• Image resizing and conversion
• Least square support vector machine

Additional information

Notes on contributors

Bhupendra Singh Kirar

Bhupendra Singh Kirar received the BE degree from SATI, Vidisha India, in 2004 and MTech and PhD from MANIT Bhopal, India, in 2009 and 2019, respectively. He has over 12 years of teaching experience. He has published many papers in SCI/Scopus indexed journals. His research interest includes the area of image processing.

Dheeraj Kumar Agrawal

Dheeraj Kumar Agrawal is associate professor in the Department of ECE, MANIT, Bhopal, India. He did BE from Rajiv Gandhi Technological University, and MTech and PhD from MANIT, Bhopal, India, respectively. He has over 15 years of teaching experience. He has published many papers in SCI/Scopus indexed journals. His research interest includes the area of image processing. Email: [email protected]

Seema Kirar

Seema Kirar is assistant professor in the Department of ECE, BIST Bhopal, India. She received the MTech degree from MITS, Gwalior, India, in 2008. She has over 10 years of teaching experience in the field of ECE. Her research interest includes the area of image processing. Email: [email protected]