Abstract
In order to reveal discriminant information from the multi-lead ECG to facilitate the ECG biometric recognition, two novel feature extraction algorithms are proposed in this paper. As opposed to the existing singlelead based techniques, the proposed algorithms which rely on the idea of block projection allow the features to be extracted without breaking the structure between the leads so that more information can be exploited for recognition. In addition, the algorithms require only one fiducial point (i.e., R peaks) to be determined and are applicable to any multi-lead ECG regardless of its number of leads. Detailed experiments show that the proposed algorithms outperform the existing single-lead based approaches.