Fingerprint Classification Using Region Partition

Saparudin, Saparudin and Abdiansah, Abdiansah (2010) Fingerprint Classification Using Region Partition. In: The 2010 International Conference on Informatics Cypernetics, and Computer Applications (ICICCA2010), July 19-21, 2010, Bangalore, India.

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Abstract

Fingerprint classification is a technique that used for supporting of speed in fingeprint identification. Large databases of fingerprint is one of difficult problem in fingerprint research area. The more classes of fingerprint will be increased speed of fingeprint identification process. This paper will be explain results of our reseach in fingerprint classification using Region Partition Method to create sub-classes from existent classes (Left Loop, Right Loop, Twin Loop dan Whorl). Fingerprint data has been taken from NIST databases with 30 sample for each class, total sample is 120 sample. There are three stages that are used in this research: 1) segmentation; 2) Orientation Estimate; and 3) Region Partition. The results is gained new sub-classes where Twin Loop class have many sub-classes than others.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA75 Electronic computers. Computer science
Divisions: 09-Faculty of Computer Science > 57201-Information Systems (S1)
Depositing User: Abdiansah Abdiansah
Date Deposited: 25 Sep 2019 05:16
Last Modified: 25 Sep 2019 05:16
URI: http://repository.unsri.ac.id/id/eprint/8325

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