Next Article in Journal
Novel Gyroscopic Mounting for Crystal Oscillators to Increase Short and Medium Term Stability under Highly Dynamic Conditions
Previous Article in Journal
Synthesis and Gas Sensing Properties of Single La-Doped SnO2 Nanobelts
Article Menu

Export Article

Open AccessArticle
Sensors 2015, 15(6), 14241-14260; doi:10.3390/s150614241

Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines

1
Departamento de Ciencia de los Materiales e Ingeniería Metalúrgica, Expresión Gráfica de la Ingeniería, Ingeniería Cartográfica, Geodesia y Fotogrametría, Ingeniería Mecánica e Ingeniería de los Procesos de Fabricación, Área de Ingeniería Mecánica, Universidad de Valladolid, Paseo del Cauce 59, 47011 Valladolid, Spain
2
Departamento de Teoría de la Señal y Comunicaciones e Ingeniería Telemática, Universidad de Valladolid, Paseo Belén 15, 47011 Valladolid, Spain
3
Informática, Universidad Pontificia de Salamanca, Calle Compañía 5, 37002 Salamanca, Spain
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M.N. Passaro
Received: 6 May 2015 / Revised: 8 June 2015 / Accepted: 10 June 2015 / Published: 17 June 2015
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [1122 KB, uploaded 17 June 2015]   |  

Abstract

Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM). The preprocessing techniques used are spatial filtering, segmentation—based on a Gaussian Mixture Model (GMM) to separate the person from the background, masking—to reduce the dimensions of images—and binarization—to reduce the size of each image. An analysis of classification error and a study of the sensitivity of the error versus the computational burden of each implemented algorithm are presented. This allows the selection of the most relevant algorithms, according to the benefits required by the system. A significant improvement of the biometric system has been achieved by reducing the classification error, the computational burden and the storage requirements. View Full-Text
Keywords: acoustic biometric system; acoustic images; preprocessing techniques; support vector machine acoustic biometric system; acoustic images; preprocessing techniques; support vector machine
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

del Val, L.; Izquierdo-Fuente, A.; Villacorta, J.J.; Raboso, M. Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines. Sensors 2015, 15, 14241-14260.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top