The Ways of Increasing Quality of Human Recognition in Biometric Network Environment
International Journal of Intelligent Information Systems
Volume 6, Issue 5, October 2017, Pages: 56-61
Received: Sep. 26, 2017; Accepted: Oct. 13, 2017; Published: Nov. 22, 2017
Views 2430      Downloads 97
Shafagat Mahmudova, Institute of Information Technology of ANAS, Baku, Azerbaijan
Article Tools
Follow on us
In the paper general information about biometric technologies is given. The advantages of databases based on the unified platform in biometric network environment are shown. The ways of ensuring security in biometric network are clarified. The effective ways of recognition are investigated and their comparative analysis is implemented. The ways of increasing recognition in biometric network are studied and new method is suggested.
Biometric Network, Security, Recognition, Effective Ways, Increasing Quality
To cite this article
Shafagat Mahmudova, The Ways of Increasing Quality of Human Recognition in Biometric Network Environment, International Journal of Intelligent Information Systems. Vol. 6, No. 5, 2017, pp. 56-61. doi: 10.11648/j.ijiis.20170605.11
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
[1] sthash.FKdLyNn9.dpuf.
E. Jun Yoon, K, Young Yoo, A New, Biometric-based User Authentication Scheme without Using Password for Wireless Sensor Networks, IEEE 20th International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises, Paris, France, 2011 27-June 29, pp. 279 - 284.
N. Carev, “Povishenie effektivnosti raboti sotrudnikov QUVD q.”, Moskva putem vnedreniya peredovix biometriceskix texnoloqiy. Rukovoditel napravleniya, 2011.
A. K. Das, B. Bruhadeshwar, “A Biometric-Based User Authentication Scheme for Heterogeneous Wireless Sensor Networks” 2013 27th International Conference on Advanced Information Networking and Applications Workshops. Barcelona, Spain, March 25-March 28, 2013.
Eun-Jun Yoon, Kee-Young Yoo, A New Biometric-based User Authentication Scheme without Using Password for Wireless Sensor Networks / 2011 IEEE 20th International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises. Paris, France June 27-June 29, 2011.
Hemank Lamba, Ankit Sarkar, Mayank Vatsa, Richa Singh, Afzel Noore. Face recognition for look-alikes: A preliminary study / 2011 International Joint Conference on Biometrics. October 11-13, West Virginia Univeristy, USA, 2011.
V. V. Satyanrayanarayana Tallapragada, E. G. Rajan. Multilevel Network Security Based on Iris Biometric / 2010 International Conference on Advances in Computer Engineering Bangalore, India, June 20-June 21, 2010.
Grove, A. T. Geomorphic evolution of the Sahara and the Nile. In M. A. J. Williams & H. Faure (eds), The Sahara and the Nile: 21-35. Rotterdam: Balkema, 1980.
Mak-Kallok, Uoppen:, Uoppen.
Kazımov T. H., Mahmudova Sh. J. About a Method of Calculation of Importance Degree of Geometrical Characteristics to Identify a Human Face on the Basis of Photo Portraits // Computer Science and Engineering, USA, 2012, Vol. 2, No. 5, pp. 59-62.
T. H. Kazımov, Sh. J Mahmudova, “Increase of indicator values of identification systems quality on the recognition of human face on the basis of photoportraits”, Intelligent Control and Automation, USA, 2013, Vol. 4 No. 2, pp. 191-198.
D. I. Samal, V. V. Starovoytov, “Obnaruzheniye antropometricheskikh tochek litsa s pomoshch'yu fil'trov Gabora”, Sb. nauch. tr. “Tsifrovaya obrabotka izobrazheniy”. In-t tekhn. kibern. NAN Belarusi. Minsk, 2001, str. 141-150.
D. I. Samal, V. V. Starovoytov, “Podkhody i metody raspoznavaniya lyudey po fotoportretam”, ITK NANB, Minsk, 1998, № 8, 54 s.
V. A. Kovalov, “Metod elastichnykh eksponentsial'nykh deformatsiy dlya sovmeshcheniya tsifrovykh izobrazheniy”, Sb. nauch. tr. “Tsifrovaya obrabotka izobrazheniy”. Minsk. In-t tekhn. kibern. NAN Belarusi, 1999, str. 47-156.
J. Buhmann, M. Lades and C. Malsburg, “Size and distirtion invariant object recognition by hierarchial graph matching”, Proceedings of Int. Joint Conf. on Neural Networks, 1990, pp. 411-416.
A. Burton, V. Bruce, N. Dench, “What’s the difference between men and women? Evidence from facial measurements”, Perception, 1993, No. 22, pp. 153-176.
C. Choi, K. Aizawa, H. Harashima and T. Takebe,“Analysis and synthesis of facial image sequences in model-based image coding”, IEEE Transactions on Circuits and Systems for Video Technology, 1994, vol. 4, No. 3, pp. 257-274.
S. Jeng, H. Liao, Y. Lui and M. Chern, “An efficient approach for facial feature detection using geometrical face model”, Proceedings Int. Conf. on Pattern Recognition, 1996, vol. 4, pp. 426-430.
V. V. Gilovich, I. V. Prudnikov, “Povysheniye effektivnosti raspoznavaniya lichnosti pri ispol'zovanii biometricheskoy identifikatsii”, Sistemy, seti i ustroystva telekommunikatsiy, 2011, tom 7, № 1, str. 12-16.
YU. N. Matveyev ISSN 0236-3933. Vestnik MGTU, 2012M.
C. Devi, M. Pushpa Rani, “Skull recognition using sift features”, International Journal of Advanced Technology in Engineering and Science, 2015, vol. 03, No. 01, pp. 386-392.
Science Publishing Group
1 Rockefeller Plaza,
10th and 11th Floors,
New York, NY 10020
Tel: (001)347-983-5186