A Novel Biometric Based on ECG Signals and
Images for Human Authentication
Mohamed Hammad, Mina Ibrahim and Mohiy
Hadhoud
Faculty of computers and information,
Menoufia University, Egypt
Abstract: This paper represents a complete
system for using Electrocardiogram (ECG) images for human authentication. In
this study, the proposed algorithm is divided into three main stages:
Pre-processing stage, feature extraction stage and classification stage. A real
database is used; it consists of 120 ECG images which are collected from 20
persons. The preprocessing stage is done on the ECG image. Preprocessing should
remove all variations and details from an ECG image that are meaningless to the
authentication method. In addition, this paper discusses briefly an extended
version of work previously published on ECG feature extraction. In
classification stage, Neural Network is used to make persons authentication. At
the end, a system for real-time authentication is built. The proposed system
achieves high sensitivity results for extracting ECG features and for human
authentication.
Keywords: ECG image, human authentication and
neural Network.
Received March 3, 2015; accepted April 26, 2015
