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Experimental Study on the Effect of Pattern Variation and Feature Points on Fingerprint Matching


Affiliations
1 Department of Computer Science, Adekunle Ajasin University, Akungba Akoko, Nigeria
2 Department of Software Engineering, Federal University of Technology, Akure, Nigeria
 

Fingerprint has been adjudged as the most reliable means of identification and authentication of an individual because of its uniqueness, high immutability and unchanging patterns. Typically, the ridges of fingers consist of different pattern types whose attributes are often extracted for matching during fingerprint classification. The occurrence of these patterns vary among fingerprint, which has significantly affected the accuracy of fingerprint recognition and classification processes. This paper therefore focuses on the investigation of the impact of pattern variation, singular points and feature points on fingerprint matching. The investigation was based on benchmarked FVC2000, FVC2002, FVC2004 and FVC2006 fingerprint databases which comprise four datasets each from different sources and of varied types. The obtained false non match rate (FNMR), false match rate (FMR), total matching time (TMT) and average matching time (AMT) values revealed that use of multiple matching criteria will lead to extension in the fingerprint matching time.

Keywords

fingerprint, pattern variation, singular point, features, matching
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  • Experimental Study on the Effect of Pattern Variation and Feature Points on Fingerprint Matching

Abstract Views: 100  |  PDF Views: 33

Authors

Oluwatayo Samuel Ogunlana
Department of Computer Science, Adekunle Ajasin University, Akungba Akoko, Nigeria
Gabriel Babatunde Iwasokun
Department of Software Engineering, Federal University of Technology, Akure, Nigeria

Abstract


Fingerprint has been adjudged as the most reliable means of identification and authentication of an individual because of its uniqueness, high immutability and unchanging patterns. Typically, the ridges of fingers consist of different pattern types whose attributes are often extracted for matching during fingerprint classification. The occurrence of these patterns vary among fingerprint, which has significantly affected the accuracy of fingerprint recognition and classification processes. This paper therefore focuses on the investigation of the impact of pattern variation, singular points and feature points on fingerprint matching. The investigation was based on benchmarked FVC2000, FVC2002, FVC2004 and FVC2006 fingerprint databases which comprise four datasets each from different sources and of varied types. The obtained false non match rate (FNMR), false match rate (FMR), total matching time (TMT) and average matching time (AMT) values revealed that use of multiple matching criteria will lead to extension in the fingerprint matching time.

Keywords


fingerprint, pattern variation, singular point, features, matching

References