28-02-2013, 01:04 PM
Multimodel Biometric Authentication System Using Fingerprint And Iris
Multimodel Biometric.ppt (Size: 3.65 MB / Downloads: 37)
Abstract
The basic aim of a biometric identification system is to discriminate automatically between subjects in a reliable and dependable way, according to a specific-target application.
Multimodal biometric system is to compare behavioral traits to provide optimal FAR and FRR.
The input data used in this project is fingerprint and iris images.
In existing system which has no security and accuracy.
The project proposes an efficient multimodel biometric system provide a suitable level of application requiring a high level of protection for the data and their services.
It proposed Template level fusion algorithm resulting in a unified biometric descriptor and integrating fingerprint and iris features based on HD calculation.
Existing system:
Unimodel biometric systems is used which is not enough and would never fully serve the purpose.
Unimodel biometrics refers to the use of only one biometric modalities in a verification / identification system.
Unimodel systems are also prone to interclass similarities within large population groups
e.g. In case of identical twins, facial feature leads to inaccurate matching, as bad data may lead to a false rejection.
Proposed system:
Multimodal biometrics refers to the use of a combination of two or more biometric modalities in a verification / identification system.
Multibiometric systems can significantly improve the recognition performance.
It proposed Template level fusion algorithm based on HD calculation.
A hamming-distance-based matching algorithm deals with the unified homogenous biometric vector
Conclusion
In this paper, a template-level fusion algorithm working on a unified biometric descriptor is presented.
The result leads to a matching algorithm that is able to process fingerprint-codified templates, iris-codified templates, and iris and fingerprint-fused templates.
The frequency-based approach should consider a high number of ROIs, resulting in the whole fingerprint image coding, and consequently, in high-dimensional feature vector.
By this project it can implement a high security authentication system.