DocumentCode :
166375
Title :
Automated Fingerprint Identification System based on weighted feature points matching algorithm
Author :
Bifari, Ezdihar N. ; Elrefaei, Lamiaa A.
Author_Institution :
Fac. of Comput. & Inf. Technol., King Abdulaziz Univ., Jeddah, Saudi Arabia
fYear :
2014
fDate :
24-27 Sept. 2014
Firstpage :
2212
Lastpage :
2217
Abstract :
Most of fingerprint identification systems perform matching algorithms based on different minutiae details present in the fingerprint. Usually, minutiae are extracted from the thinned fingerprint image. Due to the image noise and different preprocessing methods, the thinned image could results in a large number of false minutiae which may decrease the performance of the system. In this paper, some existing algorithms from different studies were integrated to build Automated Fingerprint Identification System. A new matching algorithm was proposed based on feature with two points; minutiae and ridge point. In addition, each feature extracted assigned to an appropriate weight according to proposed weights table. The modified system was tested on FVC2002 DB1 set-A and all four FVC2004 set-A databases and showed that it is effective and gives excellent results that exceed the performance of classic minutiae-based matching algorithm.
Keywords :
feature extraction; fingerprint identification; image matching; FVC2002 DB1 set-A database; FVC2004 set-A database; automated fingerprint identification system; feature extraction; image noise; image preprocessing methods; minutiae detail extraction; minutiae point; ridge point; thinned fingerprint image; weight table; weighted feature point matching algorithm; Image segmentation; Integrated optics; Magnetic resonance; Open systems; Optical imaging; Optical sensors; FFT; Gabor filter; Identification system; Morphological; Ridge orientation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Computing, Communications and Informatics (ICACCI, 2014 International Conference on
Conference_Location :
New Delhi
Print_ISBN :
978-1-4799-3078-4
Type :
conf
DOI :
10.1109/ICACCI.2014.6968559
Filename :
6968559
Link To Document :
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