Mean-Discrete Algorithm for Individuality Representation
DOI:
https://doi.org/10.29304/jqcm.2021.13.1.748Keywords:
Mean-discrete Algorithm, Multi-Biometric,, feature based fusion, IdentificationAbstract
A biometric is one of the common types of pattern recognition, which acquires biometric data from a person. From these data, a feature is established and extracted where these features can be used to identify individual. Exiting works in biometric Identification concentrate on unimodal biometric identification. As such, using features that are uniquely belonging to a person would decrease fraud possibility. Hence, owing to their great accurateness, multimodal biometric systems have become more favored compared with unimodal biometric systems in identification. However, these systems are highly complex. We proposed Mean-Discrete feature-based fusion algorithm for person detection. Its viability and advantage over the unimodal biometric systems are highlighted.
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References
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[3] M. J. Burge and K. Bowyer, "Handbook of iris recognition", Springer Publishers, (2013).
[4] D. Maltoni, D. Maio, A. K. Jain and S. Prabhakar, "Handbook of fingerprint recognition", Springer Publishers, (2009).
[5] A. K. Jain, K. Nandakumar and A. Ross, "50 years of biometric research: Accomplishments, challenges, and opportunities", Pattern Recognition Letters, 79, (2016), pp. 80 – 105.
[6] Singh M., Singh R. and Ross A., "A Comprehensive Overview of Biometric Fusion", Science Direct Information Fusion, 52, (2019), pp.187-205.
[7] Spain airports implement a multi-biometric solution, https://www.secureidnews.com/news-item/ spain-airports-implement-a-multi-biometric-solution/.
[8] Multi-biometrics: the future of border control, https://www.idemia.com/news/ multi-biometrics-future-border-control-2016-04-21.
[9] A. Jain and D. Zongker, "Feature Selection: Evaluation, Application and Small Sample Performance", IEEE Trans. On Pattern Analysis and Machine Intelligence, vol. 19 (2), (1997), pp. 153 – 158.
[10] A. S. Al Waisy, R. Qahwaji, S. Ipson, S. Al Fahdawi and T. A. M. Nagem, "A multi biometric iris recognition system based on a deep learning approach", Pattern Anal Applic, vol. 21, (2018), pp. 783–802.
[11] B. Lakshmi Priya and M. Pushpa Rani. "Authentication of Identical Twins Using Tri Modal Matching", World Congress on Computing and Communication Technologies (WCCCT), IEEE, vol. 1, (2019), pp. 30-33.
[12] W. Kabir, A. Omair, M. and M. N. S. Swamy, "Normalization and Weighting Techniques Based on Genuine-impostor Score Fusion in Multi-biometric Systems", IEEE Trans. Inf. Forensics Secur., vol. 13, (8), (2018), pp. 1989-2000.
[13] G. S. Walia, T. Singh, K. Singh and N. Verma, "Robust Multimodal Biometric System based on Optimal Score Level Fusion Model", Expert Syst. Appl., (2019), pp. 116, 364–376.
[14] A. Mansour, M. Sadik, E. Sabir and M. Jebbar, "AMBAS: An autonomous multimodal biometric authentication system", Int. J. Auton. Adapt. Commun. Syst., vol. 12, (2019), pp. 187–217.
[15] A. Basma, B. Larbi, B. Toufik and R. Messaoud, "Face–Iris Multimodal Biometric Identification System", Electronics, vol. 9 (1), (2020), pp. 85.
[16] Trier and A. K. Jain. "Feature Extraction Methods for Character Recognition- A Survey", Pattern Recognition, vol. 29 (4), (1996), pp. 641- 662.
[17] H. Takahashi, "A Neural Net OCR using geometrical and zonal pattern features", In Proc. 1th. Conf. Document Analysis and Recognition, (1991), pp. 821-828.
[18] K. Azmi, R. Kabir and E. Badi, "Recognition Printed Letters wit Zonong Features", Iran Computer Group, vol. 1, (2003), pp. 29-37.
[19] R. Muralidharan and C. Chandrasekar, "Combining local and global feature for object recognition using SVM KNN", International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012), pp. 215-219.
[20] K. M. Azah, S. M. Shamsuddin and A. Abrahamz, "Improvement of authorship invarianceness for individuality representation in writer identification", Neural Network World, vol. 3, (2010), pp. 371-387.
[21] B. O. Mohammed and S. M. Shamsuddin, "Twins multimodal biometric identification system with aspect united moment invariant", Journal of Theoretical and Applied Information Technology, vol. 95, (2017), pp. 2895.
[22] L. Wong Yee, S. M. Shamsuddin, "Multimodal Biometric Identification with Improved Discretization based Matching Score Fusion Scheme", PhD thesis. UTM, (2015).
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Published
2021-01-26
How to Cite
Mohammed, B. O. (2021). Mean-Discrete Algorithm for Individuality Representation. Journal of Al-Qadisiyah for Computer Science and Mathematics, 13(1), Comp Page 1 – 10. https://doi.org/10.29304/jqcm.2021.13.1.748
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Computer Articles
