Fundus Image Classification: A Wavelet Feature Descriptor Approach

Simple item page
dc.contributor.authorAppati, J.K.
dc.contributor.authorArmah, B.
dc.contributor.authorOwusu, E.
dc.contributor.authorSoli, M.A.T.
dc.date.accessioned2023-06-16T10:08:16Z
dc.date.available2023-06-16T10:08:16Z
dc.date.issued2023
dc.descriptionResearch Articleen_US
dc.description.abstractLately, many diabetic patients are experiencing diabetic retinopathy resulting in a loss of their sight. Even though the urgency and threat posed by this condition, there is insufficient data source to engage appropriate computational intelligence tools. The few that exist happen to be imbalanced. Leveraging on this imbalanced dataset, several activities have been carried out to propose improved detection and classification descriptors. Although some works have been done in this domain, the issue of accuracy still persists in the administration of an effective diagnosis. This paper harnessed the benefits of Gabor filters and the multi-resolution property of Discrete Wavelet Transforms (DWTs) to construct appropriate fundus feature descriptors. These discriminant features are fed into some selected but predominant classical machine learning classifiers. Numerical evaluation of the study gave a perfect (100%) average score for the fundus image classification using Gradient Boosting and Logistic Regression classifiers over Accuracy, F1-score, Precision and Recall evaluation metric. The tie in performance is further broken using their computation time, suggesting that Logistic Regression is more appropriate with 9min 32sec over Gradient Boosting or 1hr 10min 32sec.en_US
dc.identifier.otherDOI: 10.1109/ASSIC55218.2022.10088415
dc.identifier.urihttp://ugspace.ug.edu.gh:8080/handle/123456789/39277
dc.language.isoenen_US
dc.publisherIEEE Xploreen_US
dc.subjectRetinopathyen_US
dc.subjectDiscrete Wavelet Transformen_US
dc.subjectGabor feature extractionen_US
dc.subjectGradient Boostingen_US
dc.subjectLogistic Regressionen_US
dc.titleFundus Image Classification: A Wavelet Feature Descriptor Approachen_US
dc.typeArticleen_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Fundus_Image_Classification_A_Wavelet_Feature_Descriptor_Approach.pdf
Size:
519.77 KB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Department of Computer Science