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GKFCM Clustering and Classification for Low Intensity Inhomogeneity Glaucomatous Retinal Images

IJEECC Front Page

Abstract:
In the current scenario, the possibilities for the cause occurred in retina create a huge impact in day today nature. The proposed algorithm will bring a heavy monitoring of our cornea part of the body in the initial stage. The Technique follows with the feature Extraction of the Grey scale low intensity images to identifies the smoothen region of the image (640x480). Such that which will be fed as input to the clustering part(GKFCM) Gaussian Kernel Fuzzy C means clustering help in detecting the affected area of the retinal image in a simplified technique using the method call as cup and segment schema extraction, between two perspectives. This implementation of analysis is carried over for collection of images in the database (100 images), as a verification the overall clustered data will be fed as input to the SVM (support vector machine) which helps in identifying the region of affected area in prior, the performance measures paved a high powerful technique compared to the existing methodology, which yields the overall positive ration as nearly to 97% through the collected Database.
Keywords:GKFCM, SVM

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