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A hierarchical image matting model for blood vessel segmentation in retinal images

Author

Listed:
  • S. Swathi

    (Institute of Aeronautical Engineering)

  • S. Sushma

    (Institute of Aeronautical Engineering)

  • C. Devi Supraja

    (Institute of Aeronautical Engineering)

  • V. Bindusree

    (Institute of Aeronautical Engineering)

  • L. Babitha

    (Institute of Aeronautical Engineering)

  • Vallabhuni Vijay

    (Institute of Aeronautical Engineering)

Abstract

In this section, a various levelled picture matting method is utilized to extract veins from fundus pictures. All the more explicitly, a various levelled methodology is joined into the picture matting strategy for vein apportioning. For the most part, the matting strategy requires a client indicated tri map, which isolates the info picture into three districts: the frontal area, foundation, and obscure areas. Be that as it may, producing a client indicated tri map is very tuff work for vessel parcelling undertakings. In this task, we propose a technique that creates tri map consequently by using area highlights of veins. At that point, we apply a various levelled picture tangling strategy to separate the vessel components in the obscure districts. The suggested technique has less count time and performs better than numerous other regulated and solo strategies. The datasets CHASE_DB1, STARE and DRIVE are adopted as these datasets are available openly. By applying these three datasets on pictures produces fixed time of 50.71, 15.74 and 10.72 s with optimized parcelling exactness 93.9%, 94.6% and 95.1%, respectively.

Suggested Citation

  • S. Swathi & S. Sushma & C. Devi Supraja & V. Bindusree & L. Babitha & Vallabhuni Vijay, 2022. "A hierarchical image matting model for blood vessel segmentation in retinal images," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(3), pages 1093-1101, June.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:3:d:10.1007_s13198-021-01397-0
    DOI: 10.1007/s13198-021-01397-0
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    Citations

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    Cited by:

    1. Sadulla Shaik & Satish Kanapala & Vallabhuni Vijay & Chandra Shaker Pittala, 2023. "Design and performance analysis of low power and energy-efficient vedic multipliers," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(3), pages 894-902, June.
    2. Kancharapu Chaitanya & Mohammad Khadir & S. Sushma & Lavanya Nalla & G. Naveen & N. Manjula & M. Saritha & M. Lavanya & Mulinti Narendra Reddy & Vallabhuni Vijay, 2022. "Double-threshold energy detection: noisy environment applied cognitive radio," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(6), pages 2944-2948, December.

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