A novel technique for singular point detection based on Poincaré index

2011 ◽  
Author(s):  
Li Wang ◽  
Nandita Bhattacharjee ◽  
Bala Srinivasan
Keyword(s):  
Singular Point ◽  
Novel Technique ◽  
Poincaré Index ◽  
Point Detection ◽  
Poincare Index

scholarly journals Poincaré index of plane polynomial fields of third and fourth degree

2019 ◽  
Vol 55 (1) ◽  
pp. 22-31
Author(s):  
P. P. Zabreiko ◽  
A. V. Krivko-Krasko
Keyword(s):  
Singular Point ◽  
Greatest Common Divisor ◽  
Fourth Degree ◽  
Real Zeros ◽  
Poincaré Index ◽  
Poincare Index

The conditions of isolation of a zero singular point of plane polynomial fields of third and fourth degree are considered in terms of the coefficients of the components of these fields. The isolation conditions depend on the greatest common divisor of the components of polynomial fields: in some cases only on its degree, and in some cases, additionally, on the presence of nonzero real zeros. The reasoning, which allows one to write out the isolation conditions, is based on the concept of the resultant and subresultants of components of plane polynomial fields. If the zero singular point is isolated, its index is calculated through the values of subresultants and coefficients of components.

Magnetic anisotropy of RE2(Fe, Co)17 detected by singular point detection technique

Physica B+C ◽  
1977 ◽  
Vol 86-88 ◽  
pp. 210-212 ◽  
Author(s):  
R. Gröβinger ◽  
W. Steiner ◽  
F. Culetto ◽  
H. Kirchmayr
Keyword(s):  
Singular Point ◽  
Magnetic Anisotropy ◽  
Detection Technique ◽  
Point Detection

scholarly journals Core point pixel-level localization by fingerprint features in spatial domain

2022 ◽  
Vol 19 (1) ◽  
pp. 707-737
Author(s):  
Xueyi Ye ◽  
◽  
Yuzhong Shen ◽  
Maosheng Zeng ◽  
Yirui Liu ◽  
...  
Keyword(s):  
Singular Point ◽  
Reference Point ◽  
False Positive ◽  
Spatial Domain ◽  
Fingerprint Recognition ◽  
Localization Accuracy ◽  
Localization Method ◽  
Core Point ◽  
Point Detection ◽  
Fingerprint Alignment

<abstract> <p>Singular point detection is a primary step in fingerprint recognition, especially for fingerprint alignment and classification. But in present there are still some problems and challenges such as more false-positive singular points or inaccurate reference point localization. This paper proposes an accurate core point localization method based on spatial domain features of fingerprint images from a completely different viewpoint to improve the fingerprint core point displacement problem of singular point detection. The method first defines new fingerprint features, called furcation and confluence, to represent specific ridge/valley distribution in a core point area, and uses them to extract the innermost Curve of ridges. The summit of this Curve is regarded as the localization result. Furthermore, an approach for removing false Furcation and Confluence based on their correlations is developed to enhance the method robustness. Experimental results show that the proposed method achieves satisfactory core localization accuracy in a large number of samples.</p> </abstract>

scholarly journals Poincaré index and the volume functional of unit vector fields on punctured spheres

2019 ◽  
Vol 161 (3-4) ◽  
pp. 487-499
Author(s):  
Fabiano G. B. Brito ◽  
André O. Gomes ◽  
Icaro Gonçalves
Keyword(s):  
Vector Fields ◽  
Unit Vector ◽  
Volume Functional ◽  
Poincaré Index ◽  
Unit Vector Fields ◽  
Poincare Index
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