A New Approach to Fingerprint Detection Using a Combination of Minutiae Points and Invariant Moments Parameters


Sarnali Basak, Md. Imdadul Islam, M. R. Amin, Journal of Information Processing Systems Vol. 8, No. 3, pp. 421-436, Jun. 2012  

10.3745/JIPS.2012.8.3.421
Keywords: Random Variable, Skewness, Kurtosis, Invariant Moment, Termination And Bifurcation Points, Virtual Core Point
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Abstract

Different types of fingerprint detection algorithms that are based on extraction of minutiae points are prevalent in recent literature. In this paper, we propose a new algorithm to locate the virtual core point/centroid of an image. The Euclidean distance between the virtual core point and the minutiae points is taken as a random variable. The mean, variance, skewness, and kurtosis of the random variable are taken as the statistical parameters of the image to observe the similarities or dissimilarities among fingerprints from the same or different persons. Finally, we verified our observations with a moment parameter-based analysis of some previous works.


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Cite this article
[APA Style]
Sarnali Basak, Md. Imdadul Islam, & M. R. Amin (2012). A New Approach to Fingerprint Detection Using a Combination of Minutiae Points and Invariant Moments Parameters. Journal of Information Processing Systems, 8(3), 421-436. DOI: 10.3745/JIPS.2012.8.3.421.

[IEEE Style]
S. Basak, M. I. Islam and M. R. Amin, "A New Approach to Fingerprint Detection Using a Combination of Minutiae Points and Invariant Moments Parameters," Journal of Information Processing Systems, vol. 8, no. 3, pp. 421-436, 2012. DOI: 10.3745/JIPS.2012.8.3.421.

[ACM Style]
Sarnali Basak, Md. Imdadul Islam, and M. R. Amin. 2012. A New Approach to Fingerprint Detection Using a Combination of Minutiae Points and Invariant Moments Parameters. Journal of Information Processing Systems, 8, 3, (2012), 421-436. DOI: 10.3745/JIPS.2012.8.3.421.