Automatic Optic Disc Detection in Digital Fundus Images Using Image Processing Techniques

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