DocumentCode :
2559941
Title :
Support vector machine for the liquid drop fingerprint recognition
Author :
Song, Qing ; Yuan, Hui ; Liu, Xisheng ; Qiu, Chen
Author_Institution :
Autom. Sch., Beijing Univ. of Posts & Telecommun., Beijing, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
280
Lastpage :
282
Abstract :
In this paper, we introduce liquid drop fingerprint, a feature extraction method called waveform analysis and support vector machine, then discuss the recognition method of liquid drop fingerprint. The waveform analysis method can grasp the main features of the liquid drop fingerprint, greatly reduce the information needed for recognition and improve recognition efficiency. Support vector machine technology is particularly suitable for pattern classification. By using waveform analysis and support vector machine in liquid drop fingerprint recognition, we can get good results.
Keywords :
feature extraction; pattern classification; support vector machines; waveform analysis; feature extraction method; liquid drop fingerprint recognition; pattern classification; support vector machine; waveform analysis; Capacitance; Fingerprint recognition; Liquids; Optical reflection; Signal analysis; Support vector machines; Training; liquid drop fingerprint; pattern recognition; support vector machine (SVM); waveform analysis method;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
ISSN :
2157-9555
Print_ISBN :
978-1-4577-2130-4
Type :
conf
DOI :
10.1109/ICNC.2012.6234716
Filename :
6234716
Link To Document :
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