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A Novel Biometric System based on Hybrid Fusion Speech, Signature and Tongue

by Gaganpreet Kaur, Dheerendra Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 119 - Number 7
Year of Publication: 2015
Authors: Gaganpreet Kaur, Dheerendra Singh
10.5120/21082-3764

Gaganpreet Kaur, Dheerendra Singh . A Novel Biometric System based on Hybrid Fusion Speech, Signature and Tongue. International Journal of Computer Applications. 119, 7 ( June 2015), 30-39. DOI=10.5120/21082-3764

@article{ 10.5120/21082-3764,
author = { Gaganpreet Kaur, Dheerendra Singh },
title = { A Novel Biometric System based on Hybrid Fusion Speech, Signature and Tongue },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 119 },
number = { 7 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 30-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume119/number7/21082-3764/ },
doi = { 10.5120/21082-3764 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:03:27.226164+05:30
%A Gaganpreet Kaur
%A Dheerendra Singh
%T A Novel Biometric System based on Hybrid Fusion Speech, Signature and Tongue
%J International Journal of Computer Applications
%@ 0975-8887
%V 119
%N 7
%P 30-39
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

There is urgent need to make behavioural biometric systems more reliable, robust and accurate. This paper presents feature level fusion of offline signature and speech and tongue biometrics. The fusion of speech and signature with tongue made the system more efficient. MFCC is used for feature extraction in speech and in signature DCT is used which is widely used for image and texture feature extraction. While the features of tongue are extracted using SIFT algorithm. Hybrid weighted average using Apirori two item set is applied for the fusion of extracted features of all the modalities. SVC2004 signature database are used for experimental results. Tongue database was collected by capturing pictures using digital camera while for speech CMU_ARCTIC database which is available at Language Technologies Institute at Carnegie Mellon University is used in the work. Features for both noisy and non-noisy samples have been collected separately. Gaussian noise was added to the system to check the performance in noisy environment. The proposed system also works efficiently on filtered noisy modalities with accuracy of 80%. The accuracy of the noiseless system is 88. 75% with 0. 06 % of FAR and with 0. 05% of FRR and the noisy system have FAR 0. 05% and FRR 0. 15%. The ROC curves are calculated.

References
  1. Giot, R. , El-Abed, M. , Rosenberger, C. , "Fast Learning for Multibiometrics Systems using Genetic Algorithms" published in International Conference on High Performance Computing and Simulation (HPCS), Caen, France, pp. 266 – 273,DOI: 10. 1109/HPCS. 2010. 5547127,2010
  2. Md. Maruf Monwar and Marina L. Gavrilova, "Multimodal Biometric System Using Rank-Level Fusion Approach", IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, Vol. 39, No. 4, August 2009.
  3. Ross, A. , and Jain, A. K. , "Multimodal Biometrics: An Overview", published in proc. of 12th European Signal Processing Conference (EUSIPCO), Vienna, Austria, pp. 1221-1224, September 2004.
  4. Aureli Soria-Frisch, Alejandro Riera, Stephen Dune, "Fusion Operators for Multi-Modal Biometric Authentication Based On Physiological Signals".
  5. Kittler, J. , Hatef, M. , Duin, R. P. W. , and Matas, J. , "On Combining Classifiers," Pattern Analysis and Machine Intelligence, IEEE Transactions on, Vol. 20, No. 3, pp. 226-239, 1998.
  6. Margahny, M. H. , and Mitwaly, A. A. , "Fast Algorithms for Mining Association Rules," published in conference proceedings AIML 05, Cairo, Egypt, pp. 19-21, December 2005.
  7. Boullé, M. , "Khiops: A Statistical Discretization Method of Continuous Attributes", published in Journal of Machine Learning, Vol. No. 55, 2004.
  8. Agrawal, R. , Imielinksi, T. , and Swami, A. , "Mining association rules between sets of items in large databases", in proc. of the ACM SIGMOD Conference on Management of Data, pp. 207-216, 1993.
  9. Gupta, G. K. , "Introduction to Data Mining with Case Studies", Prentice Hall India, 2006.
  10. Ross, A. , and Jain, A. , "Information Fusion in Biometrics", Pattern Recognition Letters, Vol. 24, No. 13, pp. 2115-2125, 2003.
  11. Delac, K. , and Grgic, M. , "A Survey of Biometric Recognition Methods", in 46th International Symposium Electronics in Marine, ELMAR-2004, pp. 184-193, 2004.
  12. Jain, A. K. , Ross, A. , and Prabhakar, S. , "An Introduction to Biometric Recognition", IEEE Transactions on Circuits and Systems for Video Technology, Vol. 14, No. 1, pp. 1782-1793, 2004.
  13. Yaoub, S. B. , Abdeljaoued, Y. , and Mayoraz, E. , "Fusion of Face and Speech data for Person Identity Verification", IEEE Transactions on Neural Networks, Vol. 10, No. 5, pp. 1065-1074, 1999.
  14. Prabhakar, S. , and Jain, A. , "Decision-level in Fingerprint Verification", Pattern Recognition, Vol. 35, No. 4, pp. 861-874, 2001.
  15. Zanuy, M. F. , "Data Fusion in Biometrics", IEEE A & E Systems Magazine, pp. 34-38, 2005.
  16. Liu, Z. , Yan, J. Q. , Zhang, D. , and Tang, Q. L. , "A Tongue-Print Image Database For Recognition", in Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, Hong Kong, pp. 19-22,2007.
  17. Naaz, R. , Kundra, S. , Garg, P. , and Sharma, A. , "Tongue Biometric and its Application in Public Use System", IEEE 3rd International Conference on Machine Learning and Computing, Vol. 4, pp. 185-188, 2011.
  18. Diwakar, M. , and Maharishi, M. , "An Extraction and Recognition of Tongue-Print Images for Biometrics Authentication System", International Journal of Computer Applications, Vol. 61, No. 3, pp. 36-42, 2013.
  19. Karthik, P. , Prasad, R. V. S. S. , and Prasanna, S. R. M. , "Noise Robust Multimodal Biometric Person Authentication System using Face, Speech and Signature Features" , in India Conference, 2008, INDICON 2008, Annual IEEE, pp. 23-27, 2008.
  20. Jain, A. K. , and Feng, J. , "Latent Palmprint Matching", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 31, No. 6, pp. 1032-1047, 2009.
  21. Conti, V. , MiliTello, C. , Sorbello, F. , and Vitabile, S. , "A Frequency-based Approach for Features Fusion in Fingerprint and Iris Multimodal Biometric Identification Systems", IEEE Transactions on Systems, Man, and Cybernetics-Part C: Applications and Reviews, Vol. 40, No. 4, pp. 384-395, 2010.
  22. Jain, A. K. , and Feng, J. , "Latent Fingerprint Matching", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 33, No. 1, pp. 88-100, 2011.
  23. Lohane, P. U. , and Ganorkar, S. R. , "Efficient Iris and Fingerprint Fusion for Person Identification", International Journal of Computer Applications, Vol. 50, No. 17, 2012.
  24. Kaur, D. , Kaur, G. , and Singh, D. , "Efficient and Robust Multimodal Biometric System for Feature Level Fusion (Speech and Signature)", International Journal Of Computer Applications, Vol. 75, No. 5, pp. 33-38, 2013.
  25. Kaur, D. , and Kaur, G. , "Level of Fusion in Multimodal Biometrics: a Review", International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 3, Issue 2, pp. 242-246, 2013.
  26. Kaur, D. , and Kaur, G. , "Feature Level Fusion of Multimodal Biometrics for Personal Authentication", International Journal of Computers & Technology, Vol. 4, No. 2, 2013.
  27. Mohammad Reza Shahriari,Shirin Manafi,Sepehr Sadeghian, " A Novel Biometric System Based on Tongue Print Images", in International Conference on Information Warfare and Security, pp. 22-23,ISBN No. 9781908272782,2012.
  28. S. A. Angadi, Smita Gour, Gayatri Bajantri, "Offline Signature Recognition System using Radon Transform", at IEEE, Fifth International Conference on Signal and Image processing, 2014.
  29. Kaur, G. , Singh, D. , Kaur, S. , "Pollination Based Optimization for Feature Reduction at Feature Level Fusion of Speech & Signature Biometrics", at IEEE, pp. 1-6, DOI: 10. 1109/ICRITO. 2014. 7014771.
  30. Kaur, G. , Kaur, D. , and Singh, D. , "Enhancement of Security using Feature Level Fusion for Multimodal Biometrics for Speech & Signature", Published in Elsevier, pp. 25-28, ISBN No. 9789351071624.
  31. Paulino, A. A. , Feng, J. , and Jain, A. K. , "Latent Fingerprint Matching Using Descriptor-Based Hough Transform", IEEE Transactions on Information Forensics and Security, Vol. 8, No. 1, pp. 31-45, 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Biometric Multimodal Biometric SIFT Mel Frequency Cepstral Coefficient Discrete Cosine Transformation Apriori Algorithm Weighted Averaging Motion Blur filter False Acceptance Rate False Rejection Rate ROC.

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