Analysis of methods and technologies of human face recognition
DOI:
https://doi.org/10.15587/2312-8372.2017.110868Keywords:
face recognition, personality identification, biometric face recognition systemAbstract
The object of research is the processes of biometric identification and human authentication based on the image of his face for computer vision systems. One of the most problematic places in biometric identification systems using computer vision is the problem of eliminating ambiguity of «scanning». Such ambiguity arises when designing three-dimensional objects of the real world on flat images.
In the course of the research, the results of the analysis of the effects of requirements and factors on the features and characteristics of the object of the biometric face recognition system are used. First of all, it is the variability of visual images, the design of three-dimensional objects, the number and location of light sources, the color and intensity of radiation, shadows or reflections from surrounding objects. The solution to the problem of detecting objects on the image lies in the correct choice of the description of objects, for the detection and recognition of which the system is created.
Analysis of the features of classes and the properties of face recognition tasks shows that it is sufficient for a database of authentication systems to store a small set of predefined key characteristics, as much as possible characterize the images. Thus, by configuring the system to reduce the probability of incorrect identification, it is possible to use several images belonging to one person. For such purposes, a video sequence of certain specific head movements and facial muscles of the face is sufficient.
A generalized algorithm for automatic face detection and recognition is developed. The presented scheme of the generalized algorithm consists of nine simple steps and takes into account the identification features using photo and video images. The advantage of the algorithm is the simplicity of implementation, it allows already at the design stage of the identification system, to quickly evaluate the system's operability by analyzing the internal interaction of its elements.
References
- In: Jain, A. K., Bolle, R., Pankanti, S. (1999). Biometrics: Personal Identification in Networked Society. Springer US, 411. doi:10.1007/b117227
- Biometricheskaia identifikatsiia (mirovoi rynok). (May 29, 2017). Tadviser. Available at: http://www.tadviser.ru/index.php/Статья:Биометрическая_идентификация_(мировой_рынок)
- Lukashenko, V. M., Utkina, T. Yu., Verbytskyi, O. S., Lukashenko, D. A., Mitsenko, S. A., Nechyporenko, O. V. (2012). Systemnyi analiz biometrychnykh datchykiv vidbytkiv paltsia dlia systemy upravlinnia dostupom lazernoho tekhnolohichnoho kompleksu. Visnyk ChDTU, 4, 29–34.
- Lukashenko, V. M., Verbitskii, O. S., Moshchenko, S. A., Tereshchenko, Yu. Yu., Lukatskaia, E. P. (2010). Sravnitel'nyi analiz spetsializirovannyh sistem upravleniia dostupom na baze biometirii. Materiаly VІ Miedzynarodowej naukowi-praktycznej konferencji «Nauka i wyksztaicenie bez granic – 2010», 7–15 grudnia 2010, Przemysl, Poland, Vol. 22. Przemysl: Nauka i studia, 9–12.
- Ionova, A. (February 28, 2017). Tehnologii raspoznavaniia lits ili feiskontrol' po-umnomu. Novosti Interneta veshchei. Available at: https://iot.ru/gorodskaya-sreda/tekhnologii-raspoznavaniya-lits-ili-feyskontrol-po-umnomu
- Tehnologii biometricheskoi identifikatsii. (August 25, 2017). Tadviser. Available at: http://www.tadviser.ru/index.php/Статья:Технологии_биометрической_идентификации
- Kuharev, G. A., Kamenskaia, E. I., Matveev, Yu. N., Shchegoleva, N. L.; In: Hitrov, M. V. (2013). Metody obrabotki i raspoznavaniia izobrazhenii lits v zadachah biometrii. Saint Petersburg: Politehnika, 388.
- Hrulev, A. (2012). Sistemy raspoznavaniia lits. Sostoianie rynka. Perspektivy razvitiia. Sistemy bezopasnosti, 1. Available at: http://secuteck.ru/articles2/videonabl/sistemi-raspoznavaniya-lic
- Korpan, Ya. V., Nechyporenko, O. V. (2016). Metody filtratsii shumu pry obrobtsi tsyfrovoho zobrazhennia. Materialy XII Miedzynarodowej naukowi-praktycznej konferencji «Dynamika naukowych badan – 2016», 07–15 lipca, 2016, Przemysl, Poland, Vol. 13. Przemysl: Nauka i studia, 17–21.
- Korpan, Ya. V., Nechyporenko, O. V. (2016). Analiz vykorystannia tekhnolohii zmenshennia shumiv na zobrazhenni pry identyfikatsii i avtentyfikatsii obiekta. Zbirka naukovykh prats IV Naukovoi konferentsii «Fundamentalni ta prykladni doslidzhennia u suchasnii nautsi», 30 zhovtnia 2016, Kharkiv, Ukraine. Kharkiv: Technology Center, 90.
- Tropchenko, A. A., Tropchenko, A. Yu. (2015). Metody vtorichnoi obrabotki i raspoznavaniia izobrazhenii. Saint Petersburg: Universitet ITMO, 215.
- Glazunov, A. (2000). Komp'iuternoe raspoznavanie chelovecheskih lits. Otkrytye sistemy, 3. Available at: https://www.osp.ru/os/2000/03/177945/
- Savvides, M., Kumar, B. V. K. V., Khosla, P. Face Verification using Correlation Filters. CMU Electrical & Computer Engineering. Available at: http://www.ece.cmu.edu/~kumar/Biometrics_AutoID.pdf
- Marcel, S., Rodriguez, Y., Heusch, G. (2007). On the Recent Use of Local Binary Patterns for Face Authentication. International Journal of Image and Video Processing, Speci Al Issue on Facial Image Processing. Available at: http://www.idiap.ch/~marcel/professional/publications/marcel-ijivp-2007.pdf
- Li, S. Z., Jain, A. K. (2011). Handbook of Face Recognition. London: Springer, 699. doi:10.1007/978-0-85729-932-1
- Jafri, R., Arabnia, H. R. (2009). A Survey of Face Recognition Techniques. Journal of Information Processing Systems, 5 (2), 41–68. doi:10.3745/jips.2009.5.2.041
- Viola, P., Jones, M. (2001). Rapid object detection using a boosted cascade of simple features. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, Vol. 1. Kauai, Hawaii, USA, 511–518. doi:10.1109/cvpr.2001.990517
- Papageorgiou, C. P., Oren, M., Poggio, T. (1998). A general framework for object detection. Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271). Narosa Publishing House, 555–562. doi:10.1109/iccv.1998.710772
- Nechyporenko, O. V., Korpan, Ya. V. (2016). Biometrychna identyfikatsiia i avtentyfikatsiia osoby za heometriieiu oblychchia. Visnyk KhNU, 4, 133–138.
- Samal, D. I., Starovoitov, V. V. (1999). Vybor priznakov dlia raspoznavaniia na osnove statisticheskih dannyh. Tsifrovaia obrabotka zobrazhenii, 105–114.
- Samal, D. I. (2002). Algoritmy identifikatsii cheloveka po fotoportretu na osnove geometricheskih preobrazovatelei. Minsk: ITK NANB, 167.
- Chellappa, R., Wilson, C. L., Sirohey, S. (1995). Human and machine recognition of faces: a survey. Proceedings of the IEEE, 83 (5), 705–741. doi:10.1109/5.381842
- Bryliuk, D., Starovoitov, V. (2001). Application of Recirculation Neural Network and Principal Component Analysis for Face Recognition. The 2nd International Conference on Neural Networks and Artificial Intelligence. Minsk: BSUIR, 136–142. Available at: http://neuroface.narod.ru/files/npca.pdf
- Kong, H., Wang, L., Teoh, E. K., Li, X., Wang, J.-G., Venkateswarlu, R. (2005). Generalized 2D principal component analysis for face image representation and recognition. Neural Networks, 18 (5–6), 585–594. doi:10.1016/j.neunet.2005.06.041
- Samaria, F. S. (1995). Face Recognition Using Hidden Markov Models. Engineering Department, Cambridge University. Available at: https://www.repository.cam.ac.uk/handle/1810/244871
- Samal, D. I., Starovoitov, V. V. (1999). Metodika avtomatizirovannogo raspoznavaniia liudei po fotoportretam. Tsifrovaia obrabotka zobrazhenii. Minsk: Institute of Technical Cybernetics of the National Academy of Sciences of Belarus, 81–85.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2017 Olga Nechyporenko, Yaroslav Korpan
This work is licensed under a Creative Commons Attribution 4.0 International License.
The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.