Feature Level Fusion Based Bimodal Biometric Using Transformation Domine Techniques

Provided by: IOSR Journal of Engineering
Topic: Security
Format: PDF
Bimodal biometric used to authenticate a person is more accurate compared to single biometric trait. In this paper the authors propose Feature Level Fusion based Bimodal Biometric using Transformation domine techniques (FLFBBT). The algorithm uses two physiological traits viz., fingerprint and face to identify a person. The Region Of Interest (ROI) of fingerprint is obtained using preprocessing. The features of fingerprint are extracted using Dual Tree Complex Wavelet Transforms (DTCWT) by computing absolute values of high and low frequency components. The final features of fingerprint are computed by applying log on concatenated absolute value of high and low frequency components. The face image is preprocessed by cropping only face part and Discrete Wavelet Transforms (DWT) is applied.

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