A novel feature extraction method in ECG biometrics

Author

Hamdi, Takoua ; Ben Slimane, Anis ; Ben Khalifa, Anouar

Author_Institution

Nat. Eng. Sch. of Sousse, Univ. of Sousse, Sousse, Tunisia

fYear

2014

Firstpage

1

Lastpage

5

Abstract

Over the last few years, the Electrocardiogram (ECG) was introduced as a powerful biometric modality for human authentication. Indeed, ECG has some characteristics specific to each individual. In this paper we present an authentication system based on the ECG signal. We are particularly interested in the feature extraction step where we propose new approach based on the slopes and the angles of the ECG signal. The neural network is used for the classification step. The results have been validated on a database related to 100 persons. We recorded a recognition rate (RR) equals 96.44% which is an encouraging result relative to the size of the database.

Keywords

biometrics (access control); electrocardiography; feature extraction; medical signal processing; neural nets; ECG biometrics; ECG signal; authentication system; biometric modality; classification step; database; electrocardiogram; feature extraction method; feature extraction step; human authentication; neural network; recognition rate; Authentication; Biometrics (access control); Conferences; Correlation; Databases; Electrocardiography; Feature extraction; Angles; Biometric Authentication; Database; Electrocardiogram; Multi Layer Perceptron; Principal Component Analysis; Slopes;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, Applications and Systems Conference (IPAS), 2014 First International

Print_ISBN

978-1-4799-7068-1

Type

conf

DOI

10.1109/IPAS.2014.7043304

Filename

7043304