Fingerprint Classification Based On the Entropy of Ridges


The KIPS Transactions:PartB , Vol. 10, No. 5, pp. 497-502, Aug. 2003
10.3745/KIPSTB.2003.10.5.497,   PDF Download:

Abstract

Fingerprint classification plays a role of reduction of precise joining time and improvement of the accuracy in a large volume of database. Patterns of fingerprint are classified as 5 patterns : left loop, right loop, arch, whorl, and tented arch by numbers and the location of core point and delta point. The existing fingerprint classification is useful in a captured fingerprint image of core point and delta point using paper and ink. However, this system is unapplicable in modern Automatic Fingerprint Identification System (AFIS) because of problems such as size of input and way of input. To solve the problem, this study is to suggest the way of being able to improve accuracy of fingerprint by fingerprint classification based on the entropy of ridges using fingerprint captured image of core point and prove this through the experiment.


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Cite this article
[IEEE Style]
P. C. Hui, Y. G. Bae, G. C. Bae, "Fingerprint Classification Based On the Entropy of Ridges," The KIPS Transactions:PartB , vol. 10, no. 5, pp. 497-502, 2003. DOI: 10.3745/KIPSTB.2003.10.5.497.

[ACM Style]
Park Chang Hui, Yun Gyeong Bae, and Go Chang Bae. 2003. Fingerprint Classification Based On the Entropy of Ridges. The KIPS Transactions:PartB , 10, 5, (2003), 497-502. DOI: 10.3745/KIPSTB.2003.10.5.497.