ACCURATE PERSON RECOGNITION ON COMBINING SIGNATURE AND FINGERPRINT

This paper is addressing the combination of physiological and behavioral biometrics. In this we adopted multimodal approach on combining signature and fingerprint biometrics using feature level fusion with different normalization techniques to improve the performance of multimodal system. Texture features are extracted for fingerprint, pen pressure, azimuth, and altitude features are extracted for signature. Thus, classification is done using K-NN and SVM classifiers; from experimental results of two classifiers shows that multimodal approach performs well by adopting robust feature normalization technique with suitable distance measures and kernels of classifiers