An Effective Approach to Detect Hard Exudates in Color Retinal Image

Detection of hard exudates from fundus images is crucial since hard exudates are considered to be one of the most prevalent earliest signs of reti- nopathy. To overcome the obstacles in retinal exudates identification, such as: wide variability in color, illumination uneven. An effective approach is pro- posed. After preprocessing, the histogram thresholding is used to recognize the background and object, and then the Fuzzy C-Means(FCM) technique is ap- plied to assign the pixels remain unclassified in the last stage. The algorithm performance was assessed using a Standard Diabetic Retinopathy Database DIARETDB0. The proposed algorithm obtains a sensitivity of 84.8% and a predictive value of 87.5% using lesion-based criterion, The experimental re- sults show that the proposed approach can detect hard exudates effectively.

[1]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[2]  Xiaohui Zhang,et al.  Detection and classification of bright lesions in color fundus images , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[3]  K. Prasad,et al.  Automatic Detection of Hard Exudates in Diabetic Retinopathy Using Morphological Segmentation and Fuzzy Logic , 2008 .

[4]  David R. Bull,et al.  Projective image restoration using sparsity regularization , 2013, 2013 IEEE International Conference on Image Processing.

[5]  B. Thomas,et al.  Automated identification of diabetic retinal exudates in digital colour images , 2003, The British journal of ophthalmology.

[6]  C. J. Taylor,et al.  Image analysis of fundus photographs. The detection and measurement of exudates associated with diabetic retinopathy. , 1989, Ophthalmology.

[7]  Roberto Hornero,et al.  A novel automatic image processing algorithm for detection of hard exudates based on retinal image analysis. , 2008, Medical engineering & physics.

[8]  C. Sinthanayothin,et al.  Automated localisation of the optic disc, fovea, and retinal blood vessels from digital colour fundus images , 1999, The British journal of ophthalmology.

[9]  Pascale Massin,et al.  A contribution of image processing to the diagnosis of diabetic retinopathy-detection of exudates in color fundus images of the human retina , 2002, IEEE Transactions on Medical Imaging.

[10]  Efficacy and reliability of fundus digital camera as a screening tool for diabetic retinopathy in Kuwait. , 2003, Journal of diabetes and its complications.

[11]  Chanjira Sinthanayothin,et al.  Image analysis for automatic diagnosis of diabetic retinopathy. , 1999 .