Real time Implementation of Face Recognition System on Raspberry Pi

  • Authors

    • K Raju
    • Dr Y.Srinivasa Rao
    2018-04-15
    https://doi.org/10.14419/ijet.v7i2.17.11564
  • .

  • Abstract

    Face Recognition is the ability to find and detect a person by their facial attributes. Face is a multi dimensional and thus requires a considerable measure of scientific calculations. Face recognition system is very useful and important for security, law authorization applications, client confirmation and so forth. Hence there is a need for an efficient and cost effective system. There are numerous techniques that are as of now proposed with low Recognition rate and high false alarm rate. Hence the major task of the research is to develop face recognition system with improved accuracy and improved recognition time. Our objective is to implementing Raspberry Pi based face recognition system using conventional face detection and recognition techniques such as A Haar cascade classifier is trained for detection and Local Binary Pattern (LBP) as a feature extraction technique. With the use of the Raspberry Pi kit, we go for influencing the framework with less cost and simple to use, with high performance.

     

  • References

    1. [1] Umm-E-Laila,"Comparitive study for a real time Face Recognition System Using Raspberry Pi", 4th international conferance on smart instrumentation,pages 28-30 november 2017.

      [2] S.Syed Ameer Abbas,"Realization of Multiple Human Head Detection and Direction Movement Using Raspberry Pi",IEEE WiSPNET conference, pages 1160-64,2017.

      [3] Mr. Rajesh M,"Text recognition and face detection aid for visually impaired person using raspberry pi", International Conference on circuits Power and Computing Technologies [ICCPCT],2017.

      [4] Neel Ramakant Borkar,"Real-Time Implementation Of Face Recognition System",Proceedings of the IEEE International Conference on Computing Methodologies and Communication(ICCMC),2017.

      [5] Ishita Gupta,"Face Detection and Recognition using Raspberry Pi",IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE),19-21 December 2016.

      [6] In gemar J. Cox, J. Ghosn, and P.N. Yianilos, "Highlight based face acknowledgment utilizing blend remove," in Com-puter Vision and Pattern Recognition, 1996. Continue ings CVPR '96, 1996 IEEE Computer Society Confer-ence on, 1996, pp. 209– 216.

      [7] Paola Campadelli and Raffaella Lanzarotti, "A face acknowledgment framework in view of nearby component characteri-zation.," in Advanced Studies in Biometrics, Massimo Tistarelli, Josef Bign, and Enrico Grosso, Eds. 2003, vol. 3161 of Lecture Notes in Computer Science, pp. 147– 152, Springer.

      [8] Keun-Chang Kwak and W. Pedrycz, "Face acknowledgment utilizing an upgraded free segment investigation ap-proach," Neural Networks, IEEE Transactions on, vol. 18, no. 2, pp. 530– 541, 2007.

      [9] M. Turk and A. Pentland, "Eigenfaces for acknowledgment," in Journal of Cognitive Neuroscience, 1991, vol. 3, pp. 71– 86.

      [10] P.N. Belhumeur, J.P. Hespanha, and D. Kriegman, "Eigenfaces versus fisherfaces: acknowledgment utilizing class spe-cific straight projection," Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 19, no. 7, pp. 711– 720, 1997.

      [11] Jian Yang, D. Zhang, A.F. Frangi, and Jing-Yu Yang, "Two-dimensional pca: another way to deal with appearance-based face portrayal and acknowledgment," Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 26, no. 1, pp. 131– 137, 2004.

      [12] Timo Ojala, Matti Pietikinen, and David Harwood, "A similar investigation of surface measures with classifica-tion in view of included disseminations," Pattern Recogni-tion, vol. 29, no. 1, pp. 51 – 59, 1996.

      [13] P. Viola and M. Jones, "Fast question discovery utilizing a supported course of basic highlights," in Computer Vision and Pattern Recognition, 2001. CVPR 2001. Continue ings of the 2001 IEEE Computer Society Conference on, 2001, vol. 1, pp. I– 511– I– 518 vol.1.

      [14] R. Lienhart and J. Maydt, "A broadened set of haar-like highlights for fast protest identification," in Image Process-ing. 2002. Procedures. 2002 International Conference on, 2002, vol. 1, pp. I– 900– I– 903 vol.1.

      [15] Ofir Pele and Michael Werman, "The quadratic-chi his-togram remove family," in Computer Vision ECCV 2010, Kostas Daniilidis, Petros Maragos, and Nikos Paragios, Eds. 2010, vol. 6312 of Lecture Notes in Com-puter Science, pp. 749– 762, Springer Berlin Heidelberg.

      [16] A. Barla, F. Odone, and A. Verri, "Histogram intersec-tion piece for picture order," in Image Process-ing, 2003. ICIP 2003. Procedures. 2003 International Conference on, 2003, vol. 3, pp. III– 513– 16 vol.2.

      [17] Xi Chen and Tat-Jen Cham, "Discriminative separation measures for picture coordinating," in Pattern Recognition, 2004. ICPR 2004. Procedures of the seventeenth International Conference on, 2004, vol. 3, pp. 691– 695 Vol.3.

      [18] Olegs Nikisins, "Weighted multi-scale nearby twofold pat-tern histograms for confront acknowledgment," in International Conference on Applied Mathematics and Computational Methods, AMCM 2013, 2013, pp. 76– 81.

      [19] M. Pudzs, R. Fuksis, R. Ruskuls, T. Eglitis, A. Kadikis, and M. Greitans, "Fpga based palmprint and palm vein biometric framework," in Biometrics Special Interest Group (BIOSIG), 2013 International Conference of the, 2013, pp. 1– 4.

      [20] B. Ramya Sree, M.Z. Rahman, B. Manjula, K. Murali Krishna, B.V. Rama Mohana Rao, “Analysis of an Error Detecting code in block based Transmission,†International Journal of Communication Engineering Application, E-ISSN:2230-8512, Vol 2(3), Aug.2011.

      [21] J. Divya, M.Z.Rahman, M. Ajay Kuamr and B.V. Rama Mohana Rao, “Implementation of a Complex arithmetic operation using Twin Precision,â€International Journal of Communication Engineering Application, E-ISSN: 2230-8571, Vol. 2(3), Aug.2011.

      [22] B. Bhagya Lakshmi, K. Murali Krishna, M.Z. Rahman and B.V. Rama Mohana Rao, “Implementation of High Throughput processor for Network Security Applications,†International Journal of Mobile and Wireless Communications, E-ISSN: 2230-8512, Vol. 2(3), Aug. 2011.

      [23] K. Naga Raja Kumari, K. Murali Krishna, B.V. Rama Mohana Rao, and M.Z. Rahman, “An Automatic Threshold approach based on Fuzzy Measures,†International Research Journal of Signal Processing, E-ISSN:2230-8512, Vol 2(3), Aug.2011.

      [24] Fazal Noor Basha, Md. Zia Ur Rahman, “ Comparative Analysis of Cordic Algorithm And Taylor Series Expansionâ€, Journal of Theoretical and Applied Information Technology, Vol.95, no. 9, 2017, pp.2015-2022.

      [25] Fazal Noor Basha, Md. Zia Ur Rahman, “FPGA Implementation of Cryptographic Systems for Symmetric Encryptionâ€, Journal of Theoretical and Applied Information Technology, Vol.95, no.9, 2017, pp.2038-2042.

  • Downloads

  • How to Cite

    Raju, K., & Y.Srinivasa Rao, D. (2018). Real time Implementation of Face Recognition System on Raspberry Pi. International Journal of Engineering & Technology, 7(2.17), 85-89. https://doi.org/10.14419/ijet.v7i2.17.11564

    Received date: 2018-04-15

    Accepted date: 2018-04-15

    Published date: 2018-04-15