Surface Fairing towards Regular Principal Curvature Line Networks

2019 ◽  
Vol 38 (7) ◽  
pp. 115-125
Author(s):  
Lei Chu ◽  
Pengbo Bo ◽  
Yang Liu ◽  
Wenping Wang
Keyword(s):  
Principal Curvature ◽  
Curvature Line

scholarly journals Principal Curvature-Based Region Detector for Object Recognition

2007 ◽  
Author(s):  
Hongli Deng ◽  
Wei Zhang ◽  
Eric Mortensen ◽  
Thomas Dietterich ◽  
Linda Shapiro
Keyword(s):  
Object Recognition ◽  
Principal Curvature

A Note on Elastic Surface Deformation

1951 ◽  
Vol 18 (3) ◽  
pp. 251-252
Author(s):  
Murray Kornhauser
Keyword(s):  
Principal Curvature ◽  
Surface Deformation ◽  
The Other ◽  
Elastic Surface ◽  
Elastic Bodies

Abstract Surface deformation of elastic bodies having the same modulus is treated by the standard texts on elasticity, but the applicability of the solution is limited to the range of the tables of coefficients presented. This note extends the tables to cover the range that applies to bodies having one principal curvature much larger than the other. Some inaccuracy in the tables in current use also is noted. The reader is referred to any good text on elasticity for a general discussion of this problem.

scholarly journals BLOOD VESSELS SEGMENTATION METHOD FOR RETINAL FUNDUS IMAGES BASED ON ADAPTIVE PRINCIPAL CURVATURE AND IMAGE DERIVATIVE OPERATORS

2019 ◽  
Vol XLII-2/W12 ◽  
pp. 211-218 ◽  
Author(s):  
D. N. H. Thanh ◽  
D. Sergey ◽  
V. B. Surya Prasath ◽  
N. H. Hai
Keyword(s):  
Blood Vessels ◽  
Principal Curvature ◽  
Adult Population ◽  
Ground Truth ◽  
Common Disease ◽  
Fundus Images ◽  
Central Difference ◽  
Contour Matching ◽  
Retinal Fundus Images ◽  
Retinal Fundus

<p><strong>Abstract.</strong> Diabetes is a common disease in the modern life. According to WHO’s data, in 2018, there were 8.3% of adult population had diabetes. Many countries over the world have spent a lot of finance, force to treat this disease. One of the most dangerous complications that diabetes can cause is the blood vessel lesion. It can happen on organs, limbs, eyes, etc. In this paper, we propose an adaptive principal curvature and three blood vessels segmentation methods for retinal fundus images based on the adaptive principal curvature and images derivatives: the central difference, the Sobel operator and the Prewitt operator. These methods are useful to assess the lesion level of blood vessels of eyes to let doctors specify the suitable treatment regimen. It also can be extended to apply for the blood vessels segmentation of other organs, other parts of a human body. In experiments, we handle proposed methods and compare their segmentation results based on a dataset – DRIVE. Segmentation quality assessments are computed on the Sorensen-Dice similarity, the Jaccard similarity and the contour matching score with the given ground truth that were segmented manually by a human.</p>

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