Biometric Fusion, Rank-Level
Rank level fusion is the method of consolidating more than two identification results to enhance the reliability in personal identification. In multimodal biometric system, rank level fusion can be used to combine the biometrics matching scores from the different biometric modalities (for example face, fingerprint, palmprint, and iris). It can also be used for performance improvement in unimodal biometric system by combining multiple classifier output that use different classifiers (K nearest neighbor, neural network, support vector machine, decision tree, etc.), different training set, different architectures (different number of layers or transfer function in neural network), or different parameter values (different kernels in support vector machine or different K in K nearest neighbor).
The majority of biometric system deployed using feature extraction from a single biometric modality and a particular classification...
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