Multimodal Biometric Fusion Using Face and Fingerprint

The aim of this paper is to study the fusion at feature extraction level for face and fingerprint biometrics. The proposed approach is based on the fusion of the two traits by extracting independent feature point sets from the two modalities, and making the two point sets compatible for concatenation. Multimodal biometrics refers to the use of a combination of two or more biometric modalities in a single identification system. The most compelling reason to combine different modalities is to improve the recognition accuracy. The Proposed Approach uses fast haar Transform (FHT) for the face feature Extraction while Gabor filters to obtain scale invariant features of fingerprint. We also propose novel fusion technique at feature for the fusion of the features. The proposed approach provides experimental result station the automated extraction of feature is unique and provides better result.