Multi modal verification for teleservices and security applications (M2VTS) (original) (raw)
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The Biometric systems are successfully being used in many diverse fields like identification, forensic, authorization and security systems. A brief overview of various biometric modalities is presented in this survey. Earlier uni-modal biometric systems were used which depended up on the use of a single human characteristic. Such systems had many disadvantages which led to the development of a multimodal biometric system. The multi modal biometric system uses two or more human body characteristics which results in a much higher security and authentication level. The aim of this paper is to think about different methods utilized for execution improvement, security and level of combination in multimodal biometric alongside different difficulties.
Face and Voice Authentication System
International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022
The issue of design and security is very predominant in any financial and business organization, especially such organization as a bank. Therefore, we intend to aid in security of the bank by bringing in an Artificial intelligence system that involves an individual to get an access to some items using face and voice recognition security system. This AI system is not just a normal password lock system that require a user to insert password and gain access to some items, it is a system that has an administrative authentication. In addition, with this kind of security authentication system we intend to implement, a highly secured AI feature, which enables the user with assured and highly secured transactions using their personal frame. Here an individual have to provide the face and voice authentication, which uses different algorithms, and is read by the AI server for clarification and verification. From this project, we hope to build an alternative and highly verified security for banks.
About Multi-Modal Identity Verification in Interactive Dialogue Systems
2000
The aim of this paper is to introduce multi-modal identity verification techniques to the Interactive Dialogue Systems society, and to identify possible applications. Th e multi-modal identity verification system presented here is based on two biometric modalities (speech and vision) and it uses3 experts (using voice, frontal face and profile images), based on these two modalities, in parallel. Each expert delivers as output a scalar number, called score, stating how well the claimed identity is verified. A fusion module receiving as input the 3 scores has to take a binary decision:acceptor reject identity. We have solved this fusion problem using a wide range of statistical pattern recognition techniques. The performances of the different fusion modules have been evaluated and compared on a multi-modal database, containing both vocal and visual modalities.
Multi-modal person verification tools using speech and images
Proc. Europ. Conf. on …, 1996
We propose multi-modal person veri cation using voice and images as a solution to the secured access problem. The necessary i/o devices are now standard, cheaply available and, most importantly, constitute the two most important human communication modalities. The visual part currently involves i) matching of a coarse grid containing Gabor phase information from face images, ii) facial feature localization and extraction iii) 3D biometrical feature extraction by structured light. The acoustic part uses three methods (DTW,SOSM and HMM) to compare voice references extracted from the speech signal. In the acoustic part LPC coe cients are extracted and three di erent classi ers are used in parallel. The global decision is taken by applying a Furui threshold to the individual methods and in combining the individual results according to a majority law.
A Multimodal Authentication System for Authorizing the Access to NGN Services
International conference on Networking and Services (ICNS'06), 2006
An essential feature of new generation networks is the availability of many new services offered by several different players. Often, in this scenario, different applications and services have their own authentication method and use different credentials. More reliable, flexible and easy-to-use methods are needed.
A RESEARCH FRAMEWORK FOR A MULTIMODAL BIOMETRIC AUTHENTICATION SYSTEM. doc
The Proceedings of the 3rd International Conference …, 2006
Biometric user authentication is seeing increasing use in access control systems, ranging from a simple employee attendance system to complex application such as an Epassport which utilizes fingerprints as an authenticator. There has been numerous attempts to make use of multiple biometric modality to be fused together in order to enhance the robustness and effectiveness already present in single biometric modality system. These authentication systems are known as multimodal biometric authentication systems (MMBAS). Current multimodal biometric research uses combination of modalities such as facial features, speech, retina patterns, thumb print, palm print, gait , handwriting etc. and so forth to improve on accuracy. This paper presents a research framework for a MMBAS which uses facial features, speech as well as gait. The research framework is intended to analyze how facial features, speech and gait features can be used together for an unobtrusive yet robust authentication system.
2003
Information technology innovations involve a constant evolution of man-machine interaction modes. Automated authentication of people could be used to better adapt the machine to the user. Security can also be enhanced through a better people authentication. Biometrics appears as a promising tool in these two situations. Different modalities can be envisaged, such as: fingerprint, human face images, hand shape, voice, handwritten signature... In order to take advantage of the particularities of each modality, and to improve the performance of a person authentication system, multimodality can be applied. This motivated the recording of BIOMET, a biometric database with five different modalities, including face, voice, fingerprint, hand and signature data. In this paper, the BIOMET multimodal database for person authentication is described. Details about the acquisition protocols of each modality are given. Preliminary monomodal verification results, obtained on a subcorpus of the BIOMET fingerprint data, are also presented.