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http://dx.doi.org/10.5392/JKCA.2017.17.09.132

Technical Trend Analysis of Fingerprint Classification  

Jung, Hye-Wuk (성균관대학교 정보통신대학)
Lee, Seung (성균관대학교 정보통신대학)
Publication Information
The Journal of the Korea Contents Association / v.17, no.9, 2017 , pp. 132-144 More about this Journal
Abstract
The fingerprint classification of categorizing fingerprints by classes should be used in order to improve the processing speed and accuracy in a fingerprint recognition system using a large database. The fingerprint classification methods extract features from the fingerprint ridges of a fingerprint and classify the fingerprint using learning and reasoning techniques based on the classes defined according to the flow and shape of the fingerprint ridges. In earlier days, many researches have been conducted using NIST database acquired by pressing or rolling finger against a paper. However, as automated systems using live-scan scanners for fingerprint recognition have become popular, researches using fingerprint images obtained by live-scan scanners, such as fingerprint data provided by FVC, are increasing. And these days the methods of fingerprint classification using Deep Learning have proposed. In this paper, we investigate the trends of fingerprint classification technology and compare the classification performance of the technology. We desire to assist fingerprint classification research with increasing large fingerprint database in improving the performance by mentioning the necessity of fingerprint classification research with consideration for fingerprint images based on live-scan scanners and analyzing fingerprint classification using deep learning.
Keywords
Biometrics; Fingerprint Classification; Fingerprint Identification System; Feature Extraction;
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