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Published April 28, 2016 | Version v1
Journal article Open

Fusion of Multimodal Biometrics using Feature and Score Level Fusion

Description

Biometrics is used to uniquely identify a person‘s individual based on physical and behavioural characteristics. Unimodal biometric system contains various problems such as degree of freedom, spoof attacks, non-universality, noisy data and error rates. Multimodal biometrics is introduced to overcome the limitations in Unimodal biometrics. The presented methodology extracts the features of four biometric traits such as fingerprint, palm, iris and retina. Then extracted features are fused in the form of finger print, palm and iris, retina by Discrete Wavelet Transformation. Similarity scores are generated for each fused biometric traits by using a classifier. Using both feature and score level fusion optimization problem can be solved. 

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