| Autor: |
Sanjayprabu S, Sathish Kumar R, S Jafari, Karthikamani R |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
ELCVIA Electronic Letters on Computer Vision and Image Analysis, Vol 22, Iss 2 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1577-5097 |
| DOI: |
10.5565/rev/elcvia.1677 |
| Popis: |
This paper describes the Classification of bulk OCT retinal fundus images of normal and diabetic retinopathy using the Intensity histogram features, Gray Level Co-Occurrence Matrix (GLCM), and the Gray Level Run Length Matrix (GLRLM) feature extraction techniques. Three features—Intensity histogram features, GLCM, and GLRLM were taken and, that features were compared fairly. A total of 301 bulk OCT retinal fundus color images were taken for two different varieties which are normal and diabetic retinopathy. For classification and feature extraction, a filtered image output based on a fourth-order PDE is used. Using OCT retinal fundus images, the most effective feature extraction method is identified. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
