The development of an accurate MOC algorithm without the computation of a core reference point
Abstract
Fingerprint Match-on-Card (MoC) technology offers the highest degree of security and privacy protection to cardholders as the fingerprint template never leaves the secure environment of a smart card. The level of security of a fingerprint matching system is evaluated by the type of the device which is used to compare the fingerprints. Fingerprint MoC compares the fingerprints inside the secure environment of a smart card and makes it possible for cardholders to verify themselves without the use of the central database. However it is challenging to implement an accurate fingerprint matching algorithm inside a smart card and produce an acceptable matching speed. This is due to the limited working memory and processing speed that the smart card provides. This research aimed at implementing an accurate MoC algorithm without the computation of a core reference point. This is because the core reference minutia is not reliably located in poor quality images and is not present in plain arch fingerprint classification. The research focus was on the matching accuracy and speed of the Match-on-Card fingerprint algorithm. Although the accuracy of the minutiae extractor affects the matching accuracy, minutiae extraction is out of the scope of this research. This research deployed a minutiae-based matching algorithm using multiple reference neighbourhood minutiae. The proposed algorithm used multiple reference minutiae to create neighbourhood minutiae circular tessellations. The proposed algorithm used circular tessellations to convert fingerprint features into finger codes. Finger codes are used to compare the fingerprints. The main advantage of the proposed algorithm is that it does not use the computationally intensive process of template alignment. The proposed algorithm also offers the advantages of matching speed with an Equal Error Rate (EER) of 5.5%. The experimental procedures of the proposed MoC algorithm were carried out on the public database DB1-a of Fingerprint Verification Competition 2002 (FVC2002) on a PC using MATLAB.
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