An Approach of Multi-modal Biometric Iris and Speech based Person Recognition System with Decision Fusion Technique
This paper presents a unique approach of multi-modal iris and speech feature based person recognition system. Iris images and speech signals are taken from CASIA iris database and NOIZEUS speech database respectively. Iris features are extracted after applying iris images noise removing and image pre-processing techniques. On the other hand, speech signal noise removing, start-end points detection algorithm, silence parts removal, windowing and feature extraction techniques are applied to extract the features from the speech utterance. Feature fusion is performed by combining iris and speech based feature. Principal component analysis based dimension reduction technique has been used to uni-modal iris feature vector, uni-modal speech feature and iris-speech fused feature vector. Back-propagation neural network classification technique has been used to uni-modal iris, uni-modal speech and multi-modal iris-speech techniques. These three classification outputs are fed to the voting method based decision fusion approach. CASIA iris dataset and NOIZEUS speech dataset have been used to measure the performance of multi-modal iris-speech based decision fusion approach.
Keywords: Iris-speech based multi-modal system, biometric technique, iris-speech based feature extraction, voting method
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Md. Rabiul Islam, Md. Fayzur Rahman. An Approach of Multi-modal Biometric Iris and Speech based Person Recognition System with Decision Fusion Technique. Journal of Multimedia Technology & Recent Advancements. 2015; 2(2): 5–10p.
Conti V, Milici G, Ribino P, et al. Fuzzy Fusion in Multimodal Biometric Systems. KES 2007/WIRN 2007: Lecture Notes in Artificial Intelligence #4692. 2007; 36: 108–115p. J. Daug.
Maltoni D. Biometric Fusion, Handbook of Fingerprint Recognition. 2009.
Chen, et al. An Automatic Iris Recognition System based on Fractal Dimension. VIPCC Laboratory. Department of Electrical Engineering. National Chi Nan University.
Devireddy S, et al. A Novel Approach for An Accurate Human Identification through Iris Recognition using Bitplane Slicing and Normalisation. J. Theor. Appl. Inf. Technol. 2009.
Sadaoki Furui. 50 Years of Progress in Speech and Speaker Recognition Research. ECTI Transactions on Computer and Information Technology. Nov 2005; 1(2).
Rabiner L, Juang B-H. Fundamentals of Speech Recognition. Prentice Hall, Englewood Cliffs, New Jersey. 1993.
Jacobsen J.D. Probabilistic Speech Detection. Informatics and Mathematical Modeling. DTU. 2003.
Jain A, Duin RPW, Mao J. Statistical Pattern Recognition: A Review. IEEE Trans. Pattern Anal. Machine Intell. 2002; 22(2000): 4–37p.
Davis S, Mermelstein P. Comparison of Parametric Representations for Monosyllabic Word Recognition in Continuously Spoken Sentences. IEEE 74 Trans. Acoust, Speech, Signal Processing, (ICASSP). Aug 1980; 28(4): 357–366p.
Bowyer Kevin W, Hollingsworth Karen P, Flynn Patrick J. A Survey of Iris Biometrics Research. 2008–2010. In: Handbook of Iris Recognition. Mark Burge, Bowyer Kevin W. (Ed.). Springer. 2013.
Lin J, Li J-P, Lin H, et al. Robust Person Identification with Face and Iris by Modified PUM Method. International Conference on Apperceiving Computing and Intelligence Analysis (ICACIA 2009). Oct 2009; 321–324p.
Gan J-Y, Liu J-F. Fusion and Recognition of Face and Iris Feature based on Wavelet Feature and KFDA. International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR 2009). Jul 2009; 47–50p.
Wang Z, Li Q, Niu X, et al. Multimodal Biometric Recognition Based on Complex KFDA. Fifth International Conference on Information Assurance and Security (IAS’09). Aug 2009; 2: 177–180p.
Wang ZF, Han Q, Li Q, et al. Complex Common Vector for Multimodal Biometric Recognition. Electronics Letters. May 7, 2009; 45(10): 495–496p.
Wang Z, Han Q, Niu X, et al. Feature-Level Fusion of Iris and Face for Personal Identification, Advances in Neural Networks. ISNN 2009: Lecture Notes in Computer Science #5553. 2009; 356–364p.
Wang F, Han J. Multimodal Biometric Authentication based on Score Level Fusion using Support Vector Machine. Opto-Electronics Review. Mar 2009; 17: 59–64p.
Ross A, Rattani A, Tistarelli M. Exploiting the Doddington Zoo Effect in Biometric Fusion. IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (BTAS 09). Sep 2009.
Elmadani AB. Human Authentication Using Finger Iris Algorithm Based on Statistical Approach. Second International Conference on Networked Digital Technologies (NDT 2010). 2010; 288–296p.
Wang J, Li Y, Ao X, et al. Multi-Modal Biometric Authentication Fusing Iris and Palm Print based on GMM. IEEE 15th Workshop on Statistical Signal Processing (SSP ’09). Aug 2009; 349–352p.
Borgen H, Bours P, Wolthusen S. Simulating the Influences of Aging and Ocular Disease on Biometric Recognition Performance. Advances in Biometrics: Lecture Notes in Computer Science #5558. 2009; 857–867p.
Mishra R, Pathak V. Human Recognition using Fusion of Iris and Ear Data. International Conference on Methods and Models in Computer Science (ICM2CS 2009). Dec 2009; 1–5p.
Tayal A, Balasubramaniam R, Kumar A, et al. A Multimodal Biometric Authentication System using Decision Theory, Iris and Speech Recognition. 2nd International Workshop on Nonlinear Dynamics and Synchronization (INDS’ 09). Jul 2009; 1–8p.
Tayal A, Balasubramaniam R, Kumar A, et al. A Multimodal Biometric System Coupling Iris Recognition and Speaker Identification Systems through Decision Theory. 3rd International Conference on Anti-counterfeiting, Security, and Identification in Communication (ASID 2009). Aug 2009; 135–137p.
Bhattacharjee A, Saggi M, Balasubramaniam R, et al. Decision Theory based Multimodal Biometric Authentication System using Wavelet Transform. 2009 International Conference on Machine Learning and Cybernetics. Jul 2009; 4: 2336–2342p.
Minhaz Fahim Zibran. Eye Based Authentication: Iris and Retina Recognition. Technical Report, The University of Saskatchewan, Canada. 2009.
Libor Masek. Recognition of Human Iris Patterns for Biometric Identification. The University of Western Australia. 2003.
Field David J. Relations between the Statistics of Natural Images and the Response Properties of Cortical Cells. J. Opt. Soc. Am. Dec 1987; 4(12).
Simon Doclo, Marc Moonen. On the Output SNR of the Speech-Distortion Weighted Multichannel Wiener Filter. IEEE Signal Processing Lett. Dec 2005; 12(12).
Koji Kitayama, Masataka Goto, Katunobu Itou, et al. Speech Starter: Noise-Robust Endpoint Detection by Using Filled Pauses. Eurospeech, Geneva. 2003; 1237–1240p.
Bou-Ghazale SE, Assaleh K. A Robust Endpoint Detection of Speech for Noisy Environments with Application to Automatic Speech Recognition. Proc. ICASSP 2002. 2002; 4: 3808–3811p.
Qi Li, Jinsong Zheng, Augustine Tsai, et al. Robust Endpoint Detection and Energy Normalization for Real-Time Speech and Speaker Recognition. IEEE Trans. Speech Audio Process. Mar 2002; 10(3).
Cordella LP, Foggia P, Sansone C, et al. A Real-Time Text-Independent Speaker Identification System. Proceedings of 12th International Conference on Image Analysis and Processing, IEEE Computer Society Press, Mantova, Italy. Sep 2003; 632–637p.
Picone J. Signal Modeling Techniques in Speech Recognition. Proceedings of the IEEE. 1993; 81(9): 1215–1247p.
Oppenheim AV, Schafer RW. Digital Signal Processing. Prentice Hall, Englewood Cliffs. 1975.
Dymitr Ruta, Bogdan Gabrys. An Overview of Classifier Fusion Methods. Computing and Information Systems. 2000; 7: 1–10p.
Tieniu Tan. CASIA Iris Image Database. Center for Biometrics and Security Research, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China. http://biometrics.idealtest.org/
Hu Y, Philipos CL. Evaluation of Objective Measures for Speech Enhancement. Proc. ICSLP Ninth International Conference on Spoken Language Processing (INTERSPEECH), Philadelphia, PA. 2006.
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