Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Texture analysis of optic nerve images from patients with glaucoma using wavelet transform and gray-level co- occurrence matrix (GLCM)

Not Accessible

Your library or personal account may give you access

Abstract

This paper uses a method based on the texture features computed from the wavelet transform and GLCM to discriminate between healthy and glaucomatous optic nerves. This work analyses various statistical features like contrast, energy, etc.

© 2021 The Author(s)

PDF Article
More Like This
Machine learning aided classification and grading of biopsy sample using discrete wavelet transform and gray level co-occurrence matrix

K M Sindhoora, K U Spandana, U Raghavendra, Sharada Rai, K K Mahato, and Nirmal Mazumder
JTu5A.63 Frontiers in Optics (FiO) 2022

Feature Level Fusion of Gray Dentistry Images using Haar Lifting Wavelet Transform

Jayant Bhardwaj, Abhijit Nayak, and Kulvinder Singh
MW2C.3 Mathematics in Imaging (MATH) 2017

Analysis of OCT Images to Optimize Glaucoma Diagnosis

Nahida Akter, Jack Phu, Stuart Perry, John Fletcher, Michael Kalloniatis, and Maitreyee Roy
ITh2B.2 Imaging Systems and Applications (IS) 2019

Poster Presentation

Media 1: PDF (1048 KB)     
Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.