Glaucoma Detection Based on Wavelet Transform using Fundus Images
DOI:
https://doi.org/10.15662/IJEETR.2026.0802313Keywords:
Biomedical optical imaging, feature extraction, glaucoma, Retinal Nerve Fiber Layer (RNFL), Image texture, Wavelet Transforms (WT).Abstract
Glaucoma is detected in the early stage of the diseases by identifying the intensity variation in the Retinal Nerve Fiber Layer(RNFL).The variation in the intensity was evaluated by calculating the wavelet filters (namely db3,sym3,rbio3.3,rbio3.5 and rbio3.7) coefficient and is obtained by using 2-D Discrete Wavelet Transform(DWT). DWT is good reproducibility in normal fundus images and most popular transformation technique. The proposed system is used to extract different features (namely Average Dh1,Average Dv1 and Energy) for the identification of glaucoma by using the red-free fundus images
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