International Journal of Electrical, Electronics and Data Communication (IJEEDC)
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Statistics report
Apr. 2024
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 133
Paper Published : 1712
No. of Authors : 4737
  Journal Paper


Paper Title :
Sift Feature Based Detection of Glaucoma

Author :Apeksha Avinash, K.Magesh, C. Vinoth Kumar

Article Citation :Apeksha Avinash ,K.Magesh ,C. Vinoth Kumar , (2016 ) " Sift Feature Based Detection of Glaucoma " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 1-4, Volume-4,Issue-12

Abstract : The normal and glaucomatous fundus images are classified using Support Vector Machines (SVM) and Naïve Bayes in this paper. The features of both classes of images are extracted using the Scale Invariant Feature Transform (SIFT). Two optimal features are then utilized by the SVM Classifier to classify the images into the two respective categories and its performance is compared with that of the Naive Bayes classifier. Keywords— Glaucoma, Naïve Bayes, Scale Invariant Feature Transform, Support Vector Machine.

Type : Research paper

Published : Volume-4,Issue-12


DOIONLINE NO - IJEEDC-IRAJ-DOIONLINE-6398   View Here

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