  Optic disk segmentation is a prerequisite step in automatic retinal screening
systems. In this paper, we propose an algorithm for optic disk segmentation
based on a local adaptive thresholding method. Location of the optic disk is
validated by intensity and average vessel width of retinal images. Then an
adaptive thresholding is applied on the temporal and nasal part of the optic
disc separately. Adaptive thresholding, makes our algorithm robust to
illumination variations and various image acquisition conditions. Moreover,
experimental results on the DRIVE and KHATAM databases show promising results
compared to the recent literature. In the DRIVE database, the optic disk in all
images is correctly located and the mean overlap reached to 43.21%. The optic
disk is correctly detected in 98% of the images with the mean overlap of 36.32%
in the KHATAM database.
