24-09-2010, 01:40 PM
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This article is presented by:Y.G.MANJUSHA
ABSTRACT
This topic introduces a method to authenticate people from their physiological activity, concretely the combination of ECG and EEG data.
We call this system STARFAST (STAR Fast Authentication bio-Scanner Test).
Several biometric modalities are already being exploited commercially for person authentication: voice recognition, face recognition and are among the more common Modalities now a day. But other types of fingerprint recognition biometrics are being studied as well: ADN analysis, keystroke, gait, palm print, ear shape, and hand Geometry, vein patterns, iris, retina and written signature .Although these different techniques for authentication exist now days, they present some problems. Typical biometric traits, such as fingerprint, voice and retina, are not universal, and can be subject to physical damage (dry skin, scars, loss of voice) In fact, it is estimated that 2-3% of the population is missing the feature that is required for authentication, or that the provided biometric sample is of poor quality. Furthermore, these systems are subject of attacks such as presenting a registered deceased person, dismembered body part or introduction of fake biometric samples.
New types of Biometrics, such as electroencephalography (EEG) and electrocardiography (ECG), are based on physiological signals, rather than more traditional biological traits. These have some advantages: Since every living and functional person has a recordable EEG/ECG signal, the EEG/ECG feature is universal. Moreover brain or heart damage is something that rarely occurs, so it seems to be quite invariant across time. Finally it seems very difficult to fake an EEG/ECG signature or to attack an EEG/ECG biometric system.
An ideal biometric system should present the following characteristics: 100% reliability, user friendliness, fast operation and low cost. The perfect biometric trait should have the following characteristics: very low intra-subject variability, very high inter-subject variability, very high stability over time and universality. In the next section we show the general architecture and the global performance of the system we have developed.
We call this system STARFAST (STAR Fast Authentication bio-Scanner Test).
Several biometric modalities are already being exploited commercially for person authentication: voice recognition, face recognition and are among the more common Modalities now a day. But other types of fingerprint recognition biometrics are being studied as well: ADN analysis, keystroke, gait, palm print, ear shape, and hand Geometry, vein patterns, iris, retina and written signature .Although these different techniques for authentication exist now days, they present some problems. Typical biometric traits, such as fingerprint, voice and retina, are not universal, and can be subject to physical damage (dry skin, scars, loss of voice) In fact, it is estimated that 2-3% of the population is missing the feature that is required for authentication, or that the provided biometric sample is of poor quality. Furthermore, these systems are subject of attacks such as presenting a registered deceased person, dismembered body part or introduction of fake biometric samples.
New types of Biometrics, such as electroencephalography (EEG) and electrocardiography (ECG), are based on physiological signals, rather than more traditional biological traits. These have some advantages: Since every living and functional person has a recordable EEG/ECG signal, the EEG/ECG feature is universal. Moreover brain or heart damage is something that rarely occurs, so it seems to be quite invariant across time. Finally it seems very difficult to fake an EEG/ECG signature or to attack an EEG/ECG biometric system.
An ideal biometric system should present the following characteristics: 100% reliability, user friendliness, fast operation and low cost. The perfect biometric trait should have the following characteristics: very low intra-subject variability, very high inter-subject variability, very high stability over time and universality. In the next section we show the general architecture and the global performance of the system we have developed.