TETRA TRAITS FOR EFFICIENT HUMAN RECOGNITION
TETRA TRAITS FOR EFFICIENT HUMAN RECOGNITION
ABSTRACT
This paper proposes the multimodal biometrics system for identity verification using four traits i.e., face, fingerprint, iris and signature. The proposed system is designed for applications where the training database contains a face, iris, is developed through fusion of face, fingerprint, iris and signature recognition. finally combined into a total score, which is passed to the decision module. Multimodal system then compared to the enrollment templates which are stored during database preparation for each biometric trait. Based on the proximity of feature vector and template, each subsystem computes its own matching score. These individual scores are
This system has the overall accuracy of the system is found to be more than 97%.
Keywords: Biometrics, Multimodal(Four traits) Face, Fingerprint, Iris, Signature, Fusion, Matching score
1. INTRODUCTION
“Biometrics” means “life measurement”, but the term is usually associated with the use of unique physiological characteristics to identify an individual. One of the applications which most people associate with biometrics is security. However, biometrics identification has eventually a much broader relevance as computer interface becomes more natural. It is an automated method two fingerprint images and/or one or two signature image(s) for each individual. The final decision is made by fusion at “matching score level architecture” in which feature vectors are created independently for query images and are
of recognizing a person based on a physiological or behavioral characteristic. Among the features measured are; face fingerprints, hand geometry, handwriting, iris, retinal, vein, voice etc. Biometric technologies are becoming the foundation of an extensive array of highly secure identification and personal verification solutions . As the level of security breaches and transaction
ABSTRACT
This paper proposes the multimodal biometrics system for identity verification using four traits i.e., face, fingerprint, iris and signature. The proposed system is designed for applications where the training database contains a face, iris, is developed through fusion of face, fingerprint, iris and signature recognition. finally combined into a total score, which is passed to the decision module. Multimodal system then compared to the enrollment templates which are stored during database preparation for each biometric trait. Based on the proximity of feature vector and template, each subsystem computes its own matching score. These individual scores are
This system has the overall accuracy of the system is found to be more than 97%.
Keywords: Biometrics, Multimodal(Four traits) Face, Fingerprint, Iris, Signature, Fusion, Matching score
1. INTRODUCTION
“Biometrics” means “life measurement”, but the term is usually associated with the use of unique physiological characteristics to identify an individual. One of the applications which most people associate with biometrics is security. However, biometrics identification has eventually a much broader relevance as computer interface becomes more natural. It is an automated method two fingerprint images and/or one or two signature image(s) for each individual. The final decision is made by fusion at “matching score level architecture” in which feature vectors are created independently for query images and are
of recognizing a person based on a physiological or behavioral characteristic. Among the features measured are; face fingerprints, hand geometry, handwriting, iris, retinal, vein, voice etc. Biometric technologies are becoming the foundation of an extensive array of highly secure identification and personal verification solutions . As the level of security breaches and transaction