Research Article
Cardiac Biometric Identification using Phonocardiogram Signals by Binary Decision Tree based SVM
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 105 - Issue 8 |
| Published: November 2014 |
| Authors: K. Lakshmi Devi, M. Arthanari |
10.5120/18400-9663
|
K. Lakshmi Devi, M. Arthanari . Cardiac Biometric Identification using Phonocardiogram Signals by Binary Decision Tree based SVM. International Journal of Computer Applications. 105, 8 (November 2014), 41-46. DOI=10.5120/18400-9663
@article{ 10.5120/18400-9663,
author = { K. Lakshmi Devi,M. Arthanari },
title = { Cardiac Biometric Identification using Phonocardiogram Signals by Binary Decision Tree based SVM },
journal = { International Journal of Computer Applications },
year = { 2014 },
volume = { 105 },
number = { 8 },
pages = { 41-46 },
doi = { 10.5120/18400-9663 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A K. Lakshmi Devi
%A M. Arthanari
%T Cardiac Biometric Identification using Phonocardiogram Signals by Binary Decision Tree based SVM%T
%J International Journal of Computer Applications
%V 105
%N 8
%P 41-46
%R 10.5120/18400-9663
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Analyzing Phonocardiogram signals for Automatic Identification system by Binary Decision Tree based Support Vector Machine is a new approach in the research and this paper examines the applicability of the biometric properties of the Heart Sounds. It is a highly reliable method as it cannot be forged and difficult to disguise. This reduces falsification with highly accurate results. Multi-pass Moving Average Filters (MAF) smoothes the up-sampled DWT coefficients and the peaks are detected by Averaging the Neighbors. Spectral Features are extracted and clustered by HSOM. Rough sets Theory (RST) select the best features for classification. Binary Decision Tree based Support Vector Machine is used as a classifier for recognition and Identification.
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