scholarly journals Errata: Core-point detection based on edge maps in fingerprint images

2009 ◽  
Vol 18 (2) ◽  
pp. 029801
Author(s):  
Zhihong Mao
Keyword(s):  
Core Point ◽  
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>

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