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

Sarnali Basak, Md. Imdadul Islam and M. R. Amin
Volume: 8, No: 3, Page: 421 ~ 436, Year: 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
IEEE Style
S. Basak and M. I. I. 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.