Automatic Optic Disc Detection in Digital Fundus Images Using Image Processing

Optic disc (OD) is an important part of the eye. OD detection is an important step in developing systems for automated diagnosis of various serious ophthalmic diseases like Diabetic retinopathy, Glaucoma, hypertension etc. The variation of intensity within the optic disc and intensity close to the optic disc boundary are the major hurdle in automated optic disc detection. General edge detection algorithms are frequently unsuccessful to segment the optic disc because of this. Complexity increases due to the presence of blood vessels. This paper presents simple method for OD segmentation by using techniques like principal component analysis (PCA), mathematical morphology and Watershed Transform. PCA used for good presentation of input image and mathematical morphology is used to remove blood vessels from image. Watershed Transform is used for boundary segmentation.