Detection of Abnormalities of Retina Due to Diabetic Retinopathy and Age Related Macular Degeneration Using SVM
Science Journal of Circuits, Systems and Signal Processing
Volume 5, Issue 1, February 2016, Pages: 1-7
Received: May 18, 2016; Published: May 19, 2016
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Authors
Amrita Roy Chowdhury, Computer Science and Engineering Department, West Bengal University of Technology, Salt Lake, India
Sreeparna Banerjee, Computer Science and Engineering Department, West Bengal University of Technology, Salt Lake, India; Natural Science department, West Bengal University of Technology, Salt Lake, India
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Abstract
Diabetic Retinopathy and Age related Macular Degeneration are two major retinal diseases which are creating serious concern in today’s age. Detection of preliminary signs of abnormalities due to these diseases is hard and time consuming for the ophthalmologists as the abnormal objects are very fine and small in size. As early detection of abnormalities can prevent permanent vision loss, a semi automated system is developed to detect the affected portion of retina and is tested with some retinal images. A training image set is used to train a support vector machine classifier. A test image set is given to the classifier for automatic detection of disease type. Efficiency of the classifier is tested comparing the actual value and predicted value by the classifier.
Keywords
Hard Exudates (HE), Soft Exudates (SE), Micro Aneurysms (MA), Hemorrhages (HAM), Fuzzy C Means (FCM)
To cite this article
Amrita Roy Chowdhury, Sreeparna Banerjee, Detection of Abnormalities of Retina Due to Diabetic Retinopathy and Age Related Macular Degeneration Using SVM, Science Journal of Circuits, Systems and Signal Processing. Vol. 5, No. 1, 2016, pp. 1-7. doi: 10.11648/j.cssp.20160501.11
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