Glaucoma is an eye disease. In glaucoma retinal nerve fiber layers are damaged and if it is not treated earlier then it can cause permanent vision loss. This paper represents algorithm for detection of glaucoma using retinal nerve fiber layers. For this work we have used 2D median filter and HAAR wavelet transform methods. For this work we have also used Drishti-GS dataset which contains 101 glaucomatous images and HRF (High Resolution Fundus image) database.
We have extracted the retinal nerve fiber layer Arteries. Then we have calculated its area and diameter. On the normal database we got the 100% result. We got 71.28% accuracy on glaucomatous images and when we have combined the normal and glaucomatous images then we got the 62.06% accuracy.