scholarly journals Influence of Skin Diseases on Fingerprint Recognition

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Martin Drahansky ◽  
Michal Dolezel ◽  
Jaroslav Urbanek ◽  
Eva Brezinova ◽  
Tai-hoon Kim
Keyword(s):  
Image Enhancement ◽  
Strong Influence ◽  
Skin Diseases ◽  
Point Of View ◽  
Fingerprint Recognition ◽  
Fingerprint Image ◽  
Fingerprint Image Enhancement ◽  
Electronic Sensors ◽  
Enhancement Algorithm

There are many people who suffer from some of the skin diseases. These diseases have a strong influence on the process of fingerprint recognition. People with fingerprint diseases are unable to use fingerprint scanners, which is discriminating for them, since they are not allowed to use their fingerprints for the authentication purposes. First in this paper the various diseases, which might influence functionality of the fingerprint-based systems, are introduced, mainly from the medical point of view. This overview is followed by some examples of diseased finger fingerprints, acquired both from dactyloscopic card and electronic sensors. At the end of this paper the proposed fingerprint image enhancement algorithm is described.

Fingerprint Image Enhancement Algorithm Based on FDCT

2011 ◽  
Vol 255-260 ◽  
pp. 2047-2051 ◽  
Author(s):  
Chong Ben Tao ◽  
Guo Dong Liu
Keyword(s):  
Curvelet Transform ◽  
Input Image ◽  
Recognition Algorithm ◽  
Fingerprint Recognition ◽  
Threshold Function ◽  
Fingerprint Image ◽  
Fingerprint Enhancement ◽  
Fast Discrete Curvelet Transform ◽  
Fingerprint Image Enhancement ◽  
Enhancement Algorithm

Fingerprint enhancement is an essential preprocessing step and it is crucial for the efficiency of fingerprint recognition algorithm. We present an enhancement algorithm based on fast discrete curvelet transform (FDCT). First, implement positive transform on input image, namely decompose the image into coarse scales and fine scales coefficients. Then make use of a directional filter and a soft threshold function to enhance image and reduce noise respectively. Finally, implement inverse transform, and reconstruct the enhanced image. Experiments are carried out on FVC2004 databases. For bad quality fingerprints, the results indicate that the proposed algorithm has better enhancement and de-noising effect than traditional methods, and need less time.

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