fingerprint minutiae
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2021 ◽  
Vol 13 (1) ◽  
pp. 96
Author(s):  
SuHua Wang ◽  
MingJun Cheng ◽  
ZhiQiang Ma ◽  
XiaoXin Sun


2021 ◽  
Vol 13 (1) ◽  
pp. 96
Author(s):  
ZhiQiang Ma ◽  
XiaoXin Sun ◽  
MingJun Cheng ◽  
SuHua Wang


Author(s):  
Ziad Alqadi Abdel kareem

Detailed human fingerprints, almost unique, are difficult to change and are permanent on an individual's life, making them suitable as long-term signs of human identity. They may be employed by the police or other authorities to identify individuals who wish to conceal their identity, or identify incapacitated or deceased persons and therefore cannot identify them, as in the aftermath of a natural disaster. Fingerprints images are very important data type due to wide applications requiring this type, so extraction a fingerprint identifier is a vital issue.In this paper we will analyse the fingerprints images in order to extract minutiae from the images, these minutiae will be used to construct the fingerprint identifier, the proposed procedure will be implemented and tested to ensure that the procedure generates a simple and unique identifier, which can be easily used to recognize the fingerprint in any recognition system.



2020 ◽  
Vol 98 ◽  
pp. 107054 ◽  
Author(s):  
James Moorfield ◽  
Song Wang ◽  
Wencheng Yang ◽  
Aseel Bedari ◽  
Peter Van Der Kamp


Author(s):  
Sani M. Abdullahi ◽  
Hongxia Wang ◽  
Asad Malik

Fingerprint minutiae is the unique representation of fingerprint image feature points as terminations and bifurcations. Therefore, generating a hash signature from these feature points will unarguably meet the desired properties of a robust hash signature and which will accurately fit in for fingerprint image content authentication purposes. This article proposes a novel minutiae and shape context-based fingerprint image hashing scheme. Fingerprint image minutiae points were extracted by incorporating their orientation and descriptors, then embedded into the shape context-based descriptors in order to generate a unique, compact, and robust hash signature. The robustness of the proposed scheme is determined by performing content preserving attacks, including noise addition, blurring and geometric distribution. Efficient results were achieved from the given attacks. Also, a series of evaluations on the performance comparison between the proposed and other state-of-art schemes has proven the approach to be robust and secure, by yielding a better result.



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