Fingerprint Classification by Ridgeline and Singular Point Analysis

2008 ◽  
Author(s):  
Wei Liu ◽  
Yonghui Chen ◽  
Fang Wan
Keyword(s):  
Singular Point ◽  
Fingerprint Classification ◽  
Point Analysis

scholarly journals A Customized Semantic Segmentation Network for the Fingerprint Singular Point Detection

2020 ◽  
Vol 10 (11) ◽  
pp. 3868
Author(s):  
Jiong Chen ◽  
Heng Zhao ◽  
Zhicheng Cao ◽  
Fei Guo ◽  
Liaojun Pang
Keyword(s):  
Singular Point ◽  
Semantic Segmentation ◽  
Singular Points ◽  
Detection Methods ◽  
Orientation Field ◽  
Global Features ◽  
Fingerprint Image ◽  
Detection Rates ◽  
Fingerprint Classification ◽  
Point Detection

As one of the most important and obvious global features for fingerprints, the singular point plays an essential role in fingerprint registration and fingerprint classification. To date, the singular point detection methods in the literature can be generally divided into two categories: methods based on traditional digital image processing and those on deep learning. Generally speaking, the former requires a high-precision fingerprint orientation field for singular point detection, while the latter just needs the original fingerprint image without preprocessing. Unfortunately, detection rates of these existing methods, either of the two categories above, are still unsatisfactory, especially for the low-quality fingerprint. Therefore, regarding singular point detection as a semantic segmentation of the small singular point area completely and directly, we propose a new customized convolutional neural network called SinNet for segmenting the accurate singular point area, followed by a simple and fast post-processing to locate the singular points quickly. The performance evaluation conducted on the publicly Singular Points Detection Competition 2010 (SPD2010) dataset confirms that the proposed method works best from the perspective of overall indexes. Especially, compared with the state-of-art algorithms, our proposal achieves an increase of 10% in the percentage of correctly detected fingerprints and more than 16% in the core detection rate.

Integrability of dynamical systems and the singular-point analysis

1985 ◽  
Vol 15 (6) ◽  
pp. 637-666 ◽  
Author(s):  
W. -H. Steeb ◽  
M. Kloke ◽  
B. M. Spieker ◽  
A. Kunick
Keyword(s):  
Dynamical Systems ◽  
Singular Point ◽  
Point Analysis

Hamiltonian systems with three degrees of freedom, singular-point analysis, and chaotic behavior

1986 ◽  
Vol 33 (3) ◽  
pp. 2131-2133 ◽  
Author(s):  
W.-H. Steeb ◽  
J. A. Louw ◽  
P. G. L. Leach ◽  
F. M. Mahomed
Keyword(s):  
Singular Point ◽  
Hamiltonian Systems ◽  
Degrees Of Freedom ◽  
Chaotic Behavior ◽  
Point Analysis ◽  
Three Degrees Of Freedom

Singular point analysis, resonances and Yoshida's theorem

1987 ◽  
Vol 20 (12) ◽  
pp. 4027-4030 ◽  
Author(s):  
W -H Steeb ◽  
J A Louw ◽  
M F Maritz
Keyword(s):  
Singular Point ◽  
Point Analysis
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