International Journal of Electrical, Electronics and Data Communication (IJEEDC)
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Statistics report
Dec. 2022
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 116
Paper Published : 1605
No. of Authors : 4403
  Journal Paper


Paper Title :
Retinal Blood Vessel Segmentation and Detection using K-Means and Morphological Clustering

Author :Vijaya Shanthini .K,Vinothini .K.R. M.E

Article Citation :Vijaya Shanthini .K ,Vinothini .K.R. M.E , (2017 ) " Retinal Blood Vessel Segmentation and Detection using K-Means and Morphological Clustering " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 54-57, Volume-5,Issue-4

Abstract : The Retinal image analysis through efficient detection of vessels and exudates for retinal vasculature disorder analysis. It plays important roles in detection of some diseases such as diabetes, which can be identified by analysis of the retinal blood vessels condition. It consists of two stages.First stage is blood vessel classification approach, which is used for computer based retinal image analysis to extract the retinal image vessels. The second stage is the segmentation part .Mathematical morphology and K-means clustering are used to segment the blood vessels of retina. To enhance the retinal blood vessels and subdue the background information, we perform smoothing operation on the retinal image using mathematical morphology. Index terms - Retinal images, Segmentation, Mathematical Morphology, K-means clustering.

Type : Research paper

Published : Volume-5,Issue-4


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