MULTI-MODEL BIOMETRICS AUTHENTICATION FRAMEWORK

Authentication is the process to conform the truth of an attribute claimed by real entity. Biometric technology is widely useful for the process of authentication. Today, biometric is becoming a key aspect in a multitude of applications. So this paper proposed the applications of such a multimodal biometric authentication system. Proposed system establishes a real time authentication framework using multi-model biometrics which consists of the embedded system verify the signatures, fingerprint and key pattern to authenticate the user. This is one of the most reliable, fast and cost effective tool for the user authentication

Real-time speaker verification system implemented on reconfigurable hardware

Nowadays, biometrics is considered as a promising solution in the market of security and personal verification. Applications such as financial transactions, law enforcement or network management security are already benefitting from this technology. Among the different biometric modalities, speaker verification represents an accurate and efficient way of authenticating a person’s identity by analyzing his/her voice. This identification method is especially suitable in real-life scenarios or when a remote recognition over the phone is required. The processing of a signal of voice, in order to extract its unique features, that allows distinguishing an individual to confirm or deny his/ her identity is, usually, a process characterized by a high computational cost. This complexity imposes that many systems, based on microprocessor clocked at hundreds of MHz, are unable to process samples of voice in real-time. This drawback has an important effect, since in general, the response time needed by the biometric system affects its acceptability by users. The design based on FPGA (Field Programmable Gate Arrays) is a suited way to implement systems that require a high computational capability and the resolution of algorithms in real-time. Besides, these devices allow the design of complex digital systems with outstanding performance in terms of execution time. This paper presents the implementation of a MFCC (Mel-Frequency Cepstrum Coefficients)—SVM (Support Vector Machine) speaker verification system based on a low-cost FPGA. Experimental results show that our system is able to verify a person’s identity as fast as a high-performance microprocessor based on a Pentium IV personal computer.Peer Reviewe

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Postprint (author’s final draft

Real-time speaker verification system implemented on reconfigurable hardware

Nowadays, biometrics is considered as a promising solution in the market of security and personal verification. Applications such as financial transactions, law enforcement or network management security are already benefitting from this technology. Among the different biometric modalities, speaker verification represents an accurate and efficient way of authenticating a person’s identity by analyzing his/her voice. This identification method is especially suitable in real-life scenarios or when a remote recognition over the phone is required. The processing of a signal of voice, in order to extract its unique features, that allows distinguishing an individual to confirm or deny his/ her identity is, usually, a process characterized by a high computational cost. This complexity imposes that many systems, based on microprocessor clocked at hundreds of MHz, are unable to process samples of voice in real-time. This drawback has an important effect, since in general, the response time needed by the biometric system affects its acceptability by users. The design based on FPGA (Field Programmable Gate Arrays) is a suited way to implement systems that require a high computational capability and the resolution of algorithms in real-time. Besides, these devices allow the design of complex digital systems with outstanding performance in terms of execution time. This paper presents the implementation of a MFCC (Mel-Frequency Cepstrum Coefficients)—SVM (Support Vector Machine) speaker verification system based on a low-cost FPGA. Experimental results show that our system is able to verify a person’s identity as fast as a high-performance microprocessor based on a Pentium IV personal computer.Peer Reviewe

Influencia de los segmentos del discurso en la discriminación del locutor

La autenticación de la identidad de las personas es hoy en día una tarea crucial, ya que una amplia variedad de sistemas precisan de un método fiable, bien para determinar o bien para confirmar la identidad de los individuos. Entre los métodos de autenticación, el “reconocimiento biométrico” ha recibido una considerable atención en los últimos años debido principalmente a dos motivos: el fuerte crecimiento de la demanda de aplicaciones de seguridad, tanto comerciales como militares y el rápido desarrollo de la tecnología que las soporta. Su finalidad es la determinación de la identidad de las personas basándose en uno o más rasgos físicos o de comportamiento, elementos, que a diferencia de los utilizados por otras técnicas, siempre acompañan al individuo. En este área, la utilización de la voz humana como rasgo presenta un conjunto de características que la hacen especialmente practica y la convierten en la mejor opción, cuando no la única, en un amplio conjunto de aplicaciones. El esquema general del proceso de reconocimiento define dos grandes etapas: la extracción de la información relevante de las muestras de voz capturadas, y la comparación de dicha información con otra de las mismas características previamente almacenada; comparación, esta última, para lo cual se suele hacer uso de técnicas de clasificación provenientes del área de la inteligencia artificial. Dado el estado actual de los algoritmos de clasificación, parece difícil pensar que los sistemas de reconocimiento biométrico puedan mejorar sustancialmente sus tasas a partir de la mejora de los mismos; es necesario, por tanto mejorar la calidad de la información que se les suministra. En este trabajo, el autor presenta un nuevo enfoque que permite la mejora de las tasas del reconocimiento del locutor mediante la selección de la dicha información, proponiendo, asimismo, un sencillo algoritmo que realiza este filtrado. Sus resultados no sólo son aplicables al diseño de nuevos sistemas, sino que resultan útiles a la hora de mejorar las prestaciones de los que se encuentran en funcionamiento. ---------------------------------------------The authentication of people identity is nowadays a crucial task, since a wide variety of systems requires a reliable method either to determine or to confirm the identity of individuals. Among all the authentication methods, the “biometric recognition” has received considerable attention in the recent years mainly due to two reasons: the strong growth in demand for security applications them, both commercial and military, and the rapid development of technology supporting it. Its purpose is to determine the identity of the person based on one or more physical or behavioural traits, elements that unlike those used by other techniques, always go with the individual. In this area, the use of the human voice as a trait has a set of characteristics that make it especially practical and it becomes the best choice, if not the only available one, for a wide range of applications. The general scheme of the recognition process is defined in two mayor stages: extracting the relevant information from the captured voice samples, and matching that information to another one previously stored of the same trait; matching, the latter, for which usually makes use of classification techniques inherit from the artificial intelligence area. Considering the current state of classification algorithms, it seems hard to believe that biometric recognition systems can substantially improve their rates just by improving them, it is therefore necessary to pay attention to improve the quality of information supplied. In this document, the author presents a new approach which allows the improvement of speaker recognition rates by the selection of such information, proposing, likewise, a simple algorithm that performs this filtering. Their results are not only applicable to the design of new systems, but also are useful in improving the performance of those which are in operation

Avaliação de uso do coeficientes mel-cepstrais na representação das características vocais de um locutor.

A identificação de indivíduos por meio de biometria vem sendo bastante usada como mecanismo de segurança para o acesso a sistemas computacionais ou ambientes restritos. Os sistemas biométricos têm sido desenvolvidos para realizar a identificação por impressão digital, iridia ou vocal, por exemplo. Usar a voz como meio para a autenticação individual tem sido cada vez mais possível, devido ao avanço significativo na área de Processamento Digital de Sinais de voz. Esta pesquisa tem como finalidade avaliar a eficiência dos coeficientes mel-cesptrais na representação das características de um locutor em um sistema automático de verificação de locutor. As técnicas utilizadas para a construção do sistema automático de verificação de locutor, visando a uma implementação em hardware, incluem o uso de: (i) coeficientes mel-cepstrais, na composição do vetor de características; (ii) quantização vetorial, na obtenção de padrões; e (iii) uma regra de decisão, baseada na distância Euclidiana. O sistema utilizado para a avaliação da representação das características vocais de um locutor é uma modificação de outro sistema automático de verificação de locutor que utiliza coeficientes LPC para a representação das características vocais de um locutor. Para tanto, fez-se uso das linguagens C++ (fase de treinamento) e SystemVerilog (fase de verificação). Os resultados utilizando coeficientes mel-cepstrais foram de 99,34% na taxa de acerto, 0,17% para taxa de erros e 0,49% na taxa de respostas desconhecidas, comparados, respectivamente, a 96,52% na taxa de acerto, 0,90% para taxa de erros e 2,58% na taxa de desconhecidos para coeficientes LPC.Biometric identification of individuals has been widely used as a security mechanism for accessing computer systems or restricted environments. Biometric systems have been developed to perform identification through fingerprint, iris, or voice, for example. Using the voice as a biometric identifier has been increasingly possible due to significant advances in digital processing of speech signals area. This research aims to evaluate the efficiency of mel-frequency cepstral coefficients in the representation of the characteristics of a speaker in an automatic speaker verification. The techniques used to construct the automatic speaker verification system aiming at a hardware implementation included the use of: (i) melfrequency cepstral coefficients, like feature vector; (ii) vector quantization, in patterning modelling; and (iii) a decision rule, based on Euclidean distance. The system used for evaluation in the representation of the characteristics of a speaker is a modification of another automatic speaker verification system using linear predictive coding coefficients for the representation of the vocal characteristics of a speaker. It was implemented using C++ for the training phase, and SystemVerilog for the verification phase. The results using mel-frequency cepstral coefficients were 99.34% in the hit rate, 0.17% to error rate and 0.49% to unknown response rate, compared respectively to 96.52% in success rate, 0.90% to error rate and 2.58% to unknown rate using the linear predictive coding coefficients.CNP