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http://dx.doi.org/10.3745/KIPSTB.2003.10B.5.497

Fingerprint Classification Based On the Entropy of Ridges  

Park, Chang-Hee (연세대학교 대학원 전자공학)
Yoon, Kyung-Bae (김포대학 컴퓨터계열)
Ko, Chang-Bae (경동대학 정보통신공학부)
Publication Information
The KIPS Transactions:PartB / v.10B, no.5, 2003 , pp. 497-502 More about this Journal
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 mage of core point and prove this through the experiment.
Keywords
Entropy; Biometrics; Fingerprint; Classification; Identification; Singular Point;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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