Data/hora: 06/06/2024 05:32:37

Provedor de dados: | 52
País: | Brazil
Título: | An Efficient Human Identification through MultiModal Biometric System
Autores: | Meena,K.; Malarvizhi,N.
Data: | 2016-01-01
Ano: | 2016
Palavras-chave: | Multimodal Biometrics Face Finger print Iris Contourlet transform; Classification Support Vector Machine NN classifier.
Resumo: | ABSTRACT Human identification is essential for proper functioning of society. Human identification through multimodal biometrics is becoming an emerging trend, and one of the reasons is to improve recognition accuracy. Unimodal biometric systems are affected by various problemssuch as noisy sensor data,non-universality, lack of individuality, lack of invariant representation and susceptibility to circumvention.A unimodal system has limited accuracy. Hence, Multimodal biometric systems by combining more than one biometric feature in different levels are proposed in order to enhance the performance of the system. A supervisor module combines the different opinions or decisions delivered by each subsystem and then make a final decision. In this paper, a multimodal biometrics authentication is proposed by combining face, iris and finger features. Biometric features are extracted by Local Derivative Ternary Pattern (LDTP) in Contourlet domain and an extensive evaluation of LDTP is done using Support Vector Machine and Nearest Neighborhood Classifier. The experimental evaluations are performed on a public dataset demonstrating the accuracy of the proposed system compared with the existing systems. It is observed that, the combination of face, fingerprint and iris gives better performance in terms of accuracy, False Acceptance Rate, False Rejection Rate with minimum computation time.
Tipo: | Info:eu-repo/semantics/article
Idioma: | Inglês
Identificador: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132016000300403
Editor: | Instituto de Tecnologia do Paraná - Tecpar
Relação: | 10.1590/1678-4324-2016161055
Formato: | text/html
Fonte: | Brazilian Archives of Biology and Technology  v.59 n.spe2 2016
Fonte: | info:eu-repo/semantics/openAccess