Abstract Multimodal biometric recognition systems are intended to offer authentication without compromising on security, accuracy and these systems also used to address the limitations of unimodal systems like spoofing, intra class variations, noise and non-universality. In this paper, a novel adaptive two-phase multimodal framework is proposed with face, finger and speech traits. In this work, face trait reduces the search space by retrieving few possible nearest enrolled candidates to the probe using Gabor wavelets, semi-supervised kernel discriminant analysis and two dimensional- dynamic time warping. This nonlinear face classification serves as a search space reducer and affects the True Acceptance Rate (TAR). Later, level-1 and level-2 features of fingerprint trait are fused with Dempster Shafer theory and achieved high TAR. In the second phase, to reduce FAR and to validate the user identity, a text dependent speaker verification with RBFNN classifier is proposed. Classification accuracy of the proposed method is evaluated on own and standard datasets and experimental results clearly evident that proposed technique outperforms existing techniques in terms of search time, space and accuracy.

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[41] Zhang Q., Yin Y., Zhan D., and Peng J., “A Novel Serial Multimodal Biometrics Framework 946 The International Arab Journal of Information Technology, Vol. 16, No. 5, September 2019 Based on Semi Supervised Learning Techniques,” IEEE Transactions on Information Forensics and Security, vol. 9, no. 10, pp. 1681-1694, 2014. Venkatramaphanikumar Sistla is currently working as an Assistant Professor in the department of Computer Science and Engineering at VFSTR University. He is working towards Ph.D. degree at department of Computer Science and Engineering, JNTU Hyderabad, Hyderabad. His research interests include Biometrics, Image Processing, Data Mining and Pattern recognition. He has published more than 15 research articles in reputed Conferences and Journals. He served as an Organizing Chair for one IEEE Conference and two National Conferences. Venkata Krishna Kishore Kolli received his Ph.D degree from Acharya Nagarjuna University, M.Tech in Computer Science and Engineering from Andhra University, India, and B.E from University of Madras, India. He is currently working as Professor and Dean, IT Services, VFSTR University. He got more than 25 years of teaching and research experience in the field of Computer Science and Engineering. His current research interests include Digital image processing, Biometrics, Neural Networks, Machine learning, Pattern Recognition and Data Science. He has published more than 30 journals and conference papers in these areas. He has received best teacher award for four times. He has chaired one IEEE Conference and three National conferences. Kamakshi Prasad Valurouthu received his Ph.D. from the Indian Institute of Technology (IIT) Madras in 2002, M. Tech from the Andhra University, Vizag in 1992. He is currently working as professor & Head of Department of Computer Science and Engineering, JNTU Hyderabad College of Engineering, India. His research interests include Image Processing, Speech Processing, Data Mining and Ad Hoc Networks etc. He has guided 12 Ph.D., 2 M.S and currently guiding 11 Ph.D. scholars. He is an author of three books and published more than 95 publications in reputed Journals & Conferences. He has organized several refresher courses, workshops and conferences.