Zero-crossing interval correction in tracing eye-fundus blood vessels
Pattern Recognition
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
Digital Image Processing Using MATLAB
Digital Image Processing Using MATLAB
An Approach to Identify Optic Disc in Human Retinal Images Using Ant Colony Optimization Method
Journal of Medical Systems
A Decision Support System for Automatic Screening of Non-proliferative Diabetic Retinopathy
Journal of Medical Systems
Automated Identification of Exudates and Optic Disc Based on Inverse Surface Thresholding
Journal of Medical Systems
Gradient based adaptive thresholding
Journal of Visual Communication and Image Representation
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The detection of bright objects such as optic disc (OD) and exudates in color fundus images is an important step in the diagnosis of eye diseases such as diabetic retinopathy and glaucoma. In this paper, a novel approach to automatically segment the OD and exudates is proposed. The proposed algorithm makes use of the green component of the image and preprocessing steps such as average filtering, contrast adjustment, and thresholding. The other processing techniques used are morphological opening, extended maxima operator, minima imposition, and watershed transformation. The proposed algorithm is evaluated using the test images of STARE and DRIVE databases with fixed and variable thresholds. The images drawn by human expert are taken as the reference images. The proposed method yields sensitivity values as high as 96.7%, which are better than the results reported in the literature.