Dominant Set Approach to ECG Biometrics
نویسندگان
چکیده
Electrocardiographic (ECG) signals are emerging as a recent trend in the field of biometrics. In this paper, we propose a novel ECG biometric system that combines clustering and classification methodologies. Our approach is based on dominant-set clustering, and provides a framework for outlier removal and template selection. It enhances the typical workflows, by making them better suited to new ECG acquisiton paradigms that use fingers or hand palms, which lead to signals with lower signal to noise ratio, and more prone to noise artifacts. Preliminary results show the potential of the apporach, helping to further validate the highly usable setups and ECG signals as a complementary biometric modality.
منابع مشابه
ECG-based Continuous Authentication System using Adaptive String Matching
Conventional access control systems are typically based on a single time instant authentication. However, for high-security environments, continuous user verification is needed in order to robustly prevent fraudulent or unauthorized access. The electrocardiogram (ECG) is an emerging biometric modality with the following characteristics: (i) it does not require liveliness verification, (ii) ther...
متن کاملA PCA/ICA based Fetal ECG Extraction from Mother Abdominal Recordings by Means of a Novel Data-driven Approach to Fetal ECG Quality Assessment
Background: Fetal electrocardiography is a developing field that provides valuable information on the fetal health during pregnancy. By early diagnosis and treatment of fetal heart problems, more survival chance is given to the infant.Objective: Here, we extract fetal ECG from maternal abdominal recordings and detect R-peaks in order to recognize fetal heart rate. On the next step, we find a be...
متن کاملElectrocardiogram for Biometrics by using Adaptive Multilayer Generalized Learning Vector Quantization (AMGLVQ): Integrating Feature Extraction and Classification
Electrocardiogram (ECG) signal for human identity recognition is a new area on biometrics research. The ECG is a vital signal of human body, unique, robustness to attack, universality and permanence, difference to others traditional biometrics technic. This study also proposes Adaptive Multilayer Generalized Learning Vector Quantization (AMGLVQ), that integrating feature extraction and classifi...
متن کاملHuman Identification Using QT Signal and QRS Complex of the ECG
In this paper the possibility of using the ECG signal as a Biometric feature for human identification is investigated. A test set of 550 lead I ECG traces recorded from 22 healthy people at different times are used to validate the system. The proposed system extracts special parts of the ECG signal starting from the QRS complex to the end of the T wave. Two different approaches were used to com...
متن کاملECG Biometrics: A Dissimilarity Representation Approach
Electrocardiogram (ECG) biometrics are a relatively novel trend in the field of biometric recognition, comprising 13 years of development in peer-reviewed literature. This thesis studies all the inherent processes to an ECG biometric system: pre-processing, heartbeat segmentation, feature extraction and classification. For pre-processing, two filters are proposed. Three state-of-the-art segment...
متن کامل