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Heartbeat biometrics for human authentication


Automated security is one of the major concerns of modern times. Secure and reliable authentication systems are in great demand. A biometric trait like the electrocardiogram (ECG) of a person is unique and secure. In this paper, we propose an authentication technique based on Radon transform. Here, ECG wave is considered as an image and Radon transform is applied on this image. Standardized Euclidean distance is applied on the Radon image to get a feature vector. Correlation coefficient between such two feature vectors is computed to authenticate a person. False Acceptance Ratio of the proposed system is found to be 2.19% and False Rejection Ratio is 0.128%. We have developed two more approaches based on statistical features of an ECG wave as our ground work. The result of proposed technique is compared with these two approaches and also with other state-of-the-art alternatives.

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Correspondence to Chetana Hegde.

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Hegde, C., Prabhu, H.R., Sagar, D.S. et al. Heartbeat biometrics for human authentication. SIViP 5, 485 (2011).

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  • Correlation coefficient
  • FAR
  • FRR
  • k-Means clustering
  • Pair-wise distance
  • Radon transform
  • RMSE
  • ROC
  • Statistical hypothesis testing