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Automatic Blood Vessel Segmentation Based on Adaptive Thresholding Method

Authors(2):

A. Pushpalakshmi, S. Antony Mutharasan
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This paper presents a novel unsupervised method of blood vessel segmentation by iterative algorithm using fundus photographs. There are three stages for segment the blood vessels. In first stage, the negative green plane image is preprocessed to extract the vessel enhanced image. Initial estimate of the segmentation is performed by using global thresholding. Tophat morphological reconstruction is used for extract the vessel enhanced image. In second stage, new pixels are added to the existing vessel estimate iteratively by using adaptive thresholding and the residual image is extracted by removing false edge pixels. A stopping criterion is used to terminate the iterations. In third stage, final estimated vasculature is identified at high accuracy and low computational complexity.

A. Pushpalakshmi, S. Antony Mutharasan

fundus, tophat morphological reconstruction, stopping criterion, vessel segmentation

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Publication Details

Published in : Volume 2 | Issue 2 | March-April - 2016
Date of Publication Print ISSN Online ISSN
2016-04-25 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
138-141 IJSRSET162218   Technoscience Academy

Cite This Article

A. Pushpalakshmi, S. Antony Mutharasan, "Automatic Blood Vessel Segmentation Based on Adaptive Thresholding Method", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 2, Issue 2, pp.138-141, March-April-2016.
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