Biometrics and Bioinformatics

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Literature Survey on Multimodal Biometrics


Affiliations
1 Department of Electronics and Instrumentation Engineering, Bannari Amman Institute of Technology, Sathyamangalam, India
     

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Single model biometric systems suffer from much challenge such as noisy data, non-universality and spoof attacks. Multimodal biometric systems can resolve these limitations effectively by using two or more individual modalities. Multimodal biometric is the usage of multiple biometric indicators by personal identification systems for identifying the individuals. Multimodal authentication provides more level of authentication than unimodal biometrics which uses only one biometric data such as fingerprint or face modalities or iris. In this technique fusion of iris, Fingerprint and face traits are used in order to improve the accuracy, security of the system and to identify the human. The combination of Fingerprint, iris and face biometric can achieve performance that may not be possible using a single biometric technology. This system offer the high performance and to overcome the limitation of single modal biometrics. In this multimodal biometrics feature selection, feature extraction and feature classification these all techniques are used.


Keywords

Multimodal Biometrics, Finger Print, Iris, Face, Feature Selection, Feature Extraction and Feature Classification.
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  • Literature Survey on Multimodal Biometrics

Abstract Views: 202  |  PDF Views: 4

Authors

K. S. Vairavel
Department of Electronics and Instrumentation Engineering, Bannari Amman Institute of Technology, Sathyamangalam, India
J. Yazhini
Department of Electronics and Instrumentation Engineering, Bannari Amman Institute of Technology, Sathyamangalam, India

Abstract


Single model biometric systems suffer from much challenge such as noisy data, non-universality and spoof attacks. Multimodal biometric systems can resolve these limitations effectively by using two or more individual modalities. Multimodal biometric is the usage of multiple biometric indicators by personal identification systems for identifying the individuals. Multimodal authentication provides more level of authentication than unimodal biometrics which uses only one biometric data such as fingerprint or face modalities or iris. In this technique fusion of iris, Fingerprint and face traits are used in order to improve the accuracy, security of the system and to identify the human. The combination of Fingerprint, iris and face biometric can achieve performance that may not be possible using a single biometric technology. This system offer the high performance and to overcome the limitation of single modal biometrics. In this multimodal biometrics feature selection, feature extraction and feature classification these all techniques are used.


Keywords


Multimodal Biometrics, Finger Print, Iris, Face, Feature Selection, Feature Extraction and Feature Classification.

References