DocumentCode
593144
Title
Naive Bayes Classifier Applied in Droplet Fingerprint Recognition
Author
Song Qing ; Liu Xisheng ; Yuan Hui ; Qiu Chen
Author_Institution
Autom. Sch., Beijing Univ. of Posts & Telecommun., Beijing, China
fYear
2012
fDate
6-8 Nov. 2012
Firstpage
152
Lastpage
155
Abstract
Droplet analysis technology developed rapidly, the recognition of droplet fingerprint become more and more important. In this paper, we introduce the waveform analysis method which used for feature extraction, and the principle of Naive Bayes classifier. The recognition rate of the droplet fingerprint recognition method which combines waveform analysis and Naive Bayes classifier reaches 98.765%.
Keywords
Bayes methods; feature extraction; fingerprint identification; image classification; Naive Bayes classifier; droplet analysis technology; droplet fingerprint recognition; feature extraction; waveform analysis method; Bayesian methods; Capacitance; Fingerprint recognition; Liquids; Optical reflection; Signal analysis; Training; Naive Bayes classifier; droplet fingerprint recognition; waveform analysis method;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems (GCIS), 2012 Third Global Congress on
Conference_Location
Wuhan
Print_ISBN
978-1-4673-3072-5
Type
conf
DOI
10.1109/GCIS.2012.68
Filename
6449506
Link To Document