Informatics Publishing Limited

M. Ezhilarasan ¹, G. Kumaraguru ¹, D. Balraj ¹

Affiliations
1 Department of Information Technology, Pondicherry Engineering College, IN

Abstract

As the emergence of service-oriented architecture provides a major boost for e-commerce agility, the number of available Web services is rapidly increasing. However, when there are a large number of Web services available and no single Web service satisfies the given request, one has to compose multiple web services to fulfill the goal. Web services composition refers to the process of collaborating the heterogeneous web services. Even though there are many web service composition methods exist, there is no simple, standard and scalable architecture which primarily aims to satisfy the need of user request at present. This paper presents a model of web services composition by using Finite State Machine (FSM) techniques which enables to provide effective and scalable solution for service composition by generating request satisfiable deterministic paths. FSMWC targets functional, service specific and QoS attributes which when given an information goal, attempts to find all services capable of providing the desired information. We present a model for FSM based Web Service Composition (FSMWC) and evaluate the efficiency and effectiveness of FSMWC.

Keywords

FSM–Finite State Machine, WSCA–Web Service Composition Algorithm, QoS–Quality of Service.

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M. Ezhilarasan ¹, P. Vinoth Kumar ¹, R. Nirmal Kumar ¹, K. Srinivasan ¹

Affiliations
1 Department of Information Technology, Pondicherry Engineering College, Puducherry-605014, IN

Abstract

Video Enhancement is a wide range of techniques which is used to boost the quality of the video. Video stabilization removes the redundant motion fluctuations present in the video. In this paper, we present a practical method to remove the annoying shaky motion and restructure a stabilized video sequence with good visual quality. Typically, this is achieved by applying a certain amount of corrective motion displacement onto each video frame, such that to cancel the effect of high frequency fluctuations. We present an algorithm for video stabilization comprising three operations: Global Motion Estimation, Image Smoothing, and Image De-Blurring. The experimental results show the capability of the proposed algorithm to reduce the unwanted motion and proved to give the finest results.

Keywords

Global Motion Estimation, Image Smoothing, Image De-Blurring.

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M. Ezhilarasan ¹, S. Raghavendiran ¹, R. Kushwanth ¹, B. Prasanna Kumar ¹, R. Vigneswaran ¹

Affiliations
1 Department of Information Technology, Pondicherry Engineering College, Puducherry-605 014, IN

Abstract

The fast developing trend of Information Technology and the increasing requirement for Information and Network Security have demanded for efficient personal identification systems. Biometrics is seen by many as a solution to a lot of the user identification and security problems in today„s networks. Either intentional or inadvertent, misuse or abuse of passwords is a gaping hole in the present day security system. This paper proposes multimodal biometric system for identity verification using two biometric traits such as fingerprint and iris. In this paper, Fingerprint verification is performed using Minutiae Matching Technique and Iris verification uses Daugman Algorithm along with consideration of intra-class variation in the iris pattern. The final decision is made by fusion at “Decision level” in which separate authentication decision is made for each biometric trait and these scores are then combined to make a final decision.

Keywords

Biometrics, Iris, Fingerprint, Fusion and Decision Level.

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M. Ezhilarasan ¹, S. Raghavendiran ¹, R. Kushwanth ¹, B. Prasanna Kumar ¹, R. Vigneswaran ¹

Affiliations
1 Department of Information Technology, Pondicherry Engineering College, Puducherry-605014, IN

Abstract

The fast developing trend of Information Technology and the increasing requirement for Information and Network Security have demanded for efficient personal identification systems. Biometrics is seen by many as a solution to a lot of the user identification and security problems in today‘s networks. Either intentional or inadvertent, misuse or abuse of passwords is a gaping hole in the present day security system. This paper proposes multimodal biometric system for identity verification using two biometric traits such as fingerprint and iris. In this paper, Fingerprint verification is performed using Minutiae Matching Technique and Iris verification uses Daugman Algorithm along with consideration of intra-class variation in the iris pattern. The final decision is made by fusion at "Decision level" in which separate authentication decision is made for each biometric trait and these scores are then combined to make a final decision.

Keywords

Biometrics, Iris, Fingerprint, Fusion and Decision Level.

Full Text

     

M. Ezhilarasan ¹, S. Raghavendiran ¹, R. Kushwanth ¹, B. Prasanna Kumar ¹, R. Vigneswaran ¹

Affiliations
1 Department of Information Technology, Pondicherry Engineering College, Puducherry-605014, IN

Abstract

The fast developing trend of Information Technology and the increasing requirement for Information and Network Security have demanded for efficient personal identification systems. Biometrics is seen by many as a solution to a lot of the user identification and security problems in today's networks. Either intentional or inadvertent, misuse or abuse of passwords is a gaping hole in the present day security system. This paper proposes multimodal biometric system for identity verification using two biometric traits such as fingerprint and iris. In this paper, Fingerprint verification is performed using Minutiae Matching Technique and Iris verification uses Daugman Algorithm along with consideration of intra-class variation in the iris pattern. The final decision is made by fusion at “Decision level” in which separate authentication decision is made for each biometric trait and these scores are then combined to make a final decision.

Keywords

Biometrics, Iris, Fingerprint, Fusion and Decision Level.

Full Text