FINGERPRINT IDENTIFICATION - A Support Vector Machine Approach

Terje Kristensen

Abstract

In this work a hybrid technique for classification of fingerprint identification has been developed to decrease the matching time. For classification a Support Vector Machine is described and used. Automatic Fingerprint Identification Systems are widely used today, and it is therefore necessary to find a classification system that is less time-consuming. The given fingerprint database is decomposed into four different subclasses and a SVM algorithm is used to train the system to do correct classification. The classification rate has been estimated to about 87.0 % of unseen fingerprints. The average matching time is decreased with a factor of about 3.5 compared to brute force search applied.

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Paper Citation


in Harvard Style

Kristensen T. (2010). FINGERPRINT IDENTIFICATION - A Support Vector Machine Approach . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-674-021-4, pages 451-458. DOI: 10.5220/0002694104510458


in Bibtex Style

@conference{icaart10,
author={Terje Kristensen},
title={FINGERPRINT IDENTIFICATION - A Support Vector Machine Approach},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2010},
pages={451-458},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002694104510458},
isbn={978-989-674-021-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - FINGERPRINT IDENTIFICATION - A Support Vector Machine Approach
SN - 978-989-674-021-4
AU - Kristensen T.
PY - 2010
SP - 451
EP - 458
DO - 10.5220/0002694104510458