On Performance Analysis Of Diabetic Retinopathy Classification
Sivakumar, Sanjayprabu (Sri Ramakrishna Mission Vidyalaya College of Arts and Science (Coimbatore, Índia))
Rangasamy, Sathish Kumar (Sri Ramakrishna Mission Vidyalaya College of Arts and Science (Coimbatore, Índia))
Jafari,Saeid (College of Vestsjaelland South, Mathematical and Physical Science Foundation (Slagelse, Dinamarca))
Karthikamani, Ramamoorthy (Sri Ramakrishna Engineering College (Coimbatore, Índia))

Fecha:	2023
Resumen:	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.
Derechos:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Lengua:	Anglès
Documento:	Article ; recerca ; Versió publicada
Materia:	OCT ; IHF ; GLCM ; GLRLM ; GMM
Publicado en:	ELCVIA. Electronic letters on computer vision and image analysis, Vol. 22 Núm. 2 (2023) , p. 12-25 (Regular Issue) , ISSN 1577-5097

Adreça original: https://elcvia.cvc.uab.cat/article/view/1677
DOI: 10.5565/rev/elcvia.1677

14 p, 664.7 KB

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