Biometric identification using JPEG2000 compressed ECG signals

Hung Tsai Wu, Yi Ting Wu, Wen-Whei Chang

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

In wireless telecardiology applications, electrocardiogram (ECG) signals are often represented in compressed format for efficient transmission and storage purposes. Incorporation of compressed ECG based biometric enables faster person identification as it by-passes the full decompression. This study presents a new method to combine ECG biometrics with data compression within a common JPEG2000 framework. To this end, an ECG signal is considered as an image and the JPEG2000 standard is applied for data compression. Features relating to ECG morphology and heartbeat intervals are computed directly from the compressed ECG. Different classification approaches are used for person identification. Experiments on standard ECG databases demonstrate the validity of the proposed system for biometric identification with high accuracies on both healthy and diseased subjects.

Original languageEnglish
Pages (from-to)1829-1837
Number of pages9
JournalIEICE Transactions on Information and Systems
VolumeE98D
Issue number10
DOIs
StatePublished - 1 Oct 2015

Keywords

  • ECG biometric
  • JPEG2000
  • Person identification

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