An Analysis of Minutiae Matching Strength

Author(s):  
Nalini K. Ratha ◽  
Jonathan H. Connell ◽  
Ruud M. Bolle
Keyword(s):  
2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Wai Kit Wong ◽  
Thu Soe Min ◽  
Shi Enn Chong

This paper proposed a fingerprint based school debit transaction system using minutiae matching biometric technology. This biometric cashless transaction system intensely shortens the luncheon line traffic and labour force compared to conventional cash payment system. Furthermore, contrast with card cashless transaction system, fingerprint cashless transaction system with benefit that user need not carry additional identification object and remember lengthy password. The implementation of this cashless transaction system provides a more organize, reliable and efficient way to operate the school debit transaction system. 


2013 ◽  
Vol 22 (12) ◽  
pp. 4964-4971 ◽  
Author(s):  
Fanglin Chen ◽  
Xiaolin Huang ◽  
Jie Zhou

2003 ◽  
Vol 13 (04) ◽  
pp. 263-271 ◽  
Author(s):  
B. Poorna ◽  
K. S. Easwarakumar

An efficient method for fingerprint searching using recurrent autoassociative memory is proposed. This algorithm uses recurrent autoassociative memory, which uses a connectivity matrix to find if the pattern being searched is already stored in the database. The advantage of this memory is that a big database is to be searched only if there is a matching pattern. Fingerprint comparison is usually based on minutiae matching, and its efficiency depends on the extraction of minutiae. This process may reduce the speed, when large amount of data is involved. So, in the proposed method, a simple approach has been adopted, wherein first determines the closely matched fingerprint images, and then determines the minutiae of only those images for finding the more appropriate one. The gray level value of pixels along with its neighboring ones are considered for the extraction of minutiae, which is more easier than using ridge information. This approach is best suitable when database size is large.


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