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Automatic Blood Vessel Segmentation Based on Adaptive Thresholding Method

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  • A. Pushpalakshmi
  • S. Antony Mutharasan

Abstract

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.

Suggested Citation

  • A. Pushpalakshmi & S. Antony Mutharasan, 2016. "Automatic Blood Vessel Segmentation Based on Adaptive Thresholding Method," International Journal of Scientific Research in Science, Engineering and Technology, International Journal of Scientific Research in Science, Engineering and Technology, vol. 2(2), pages 138-141, December.
    • Handle: RePEc:ijs:ijsrse:v2:y2016:i2:id:hijsrset162218
    Note: Article URL: https://ijsrset.com/IJSRSET162218
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