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Fast Person Identification Using JPEG2000 Compressed ECG Data

Authors:
Yi-Ting Wu
Hung-Tsai Wu
Wen-Whei Chang

Keywords: ECG Biometric; Person Identification; JPEG2000 Image Coding Standard.

Abstract:
The use of electrocardiogram (ECG) signals in biometric systems has been an active research topic for over a decade. In wireless telecardiology applications, compressed ECG packets are often required for efficient transmission and storage purposes. Nonetheless, compressed ECG data must be decompressed first before applying existing biometric techniques that work on the original signal. To achieve a faster patient care, we propose a new biometric technique which performs person identification in compressed-domain using one-lead ECG signals. First, we apply a preprocessor which converts one-dimensional (1-D) ECG signals to 2-D image matrices and compresses them by the JPEG2000 image coding standard. Features relating to ECG morphology were extracted directly from the JPEG2000 code-stream and then applied for indexing person identity by texture content in a known enrollment database. Experiments on standard ECG databases demonstrate the validity of the proposed compressed-domain ECG biometric system with an accuracy of 95.72%.

Pages: 144 to 148

Copyright: Copyright (c) IARIA, 2014

Publication date: July 20, 2014

Published in: conference

ISSN: 2308-3484

ISBN: 978-1-61208-365-0

Location: Paris, France

Dates: from July 20, 2014 to July 24, 2014