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

S. Swathi, S. Sushma, C. Devi Supraja, V. Bindusree, L. Babitha and Vallabhuni Vijay ()
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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

International Journal of System Assurance Engineering and Management, 2022, vol. 13, issue 3, No 5, 1093-1101

Abstract: 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.

Keywords: Fundus; Hierarchical strategy; Picture matting method; Region properties; Trimap generation; Vessel partitioning (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s13198-021-01397-0

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