Analysis and Prototype Sequences of Face Recognition Techniques in Real-Time Picture Processing

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 695)

Abstract

The present-day implementation and demand of some real-time image processing applications are to be increased in various recent technologies. Some of these techniques are related to biometric applications such as fingerprint identification, face recognition, iris scan implementation, and speech identification; instead of all these techniques, face identification is an emerging concept in biometric applications with video summarization and surveillance, computer interaction with human being, face identification, and image databases in various applications to categorize face classification. In recent days, face identification is a rapid technology, which is a criminal forensic analysis, access control policy and prison dimensionality privacy with recent approaches. So, we have gone through formalized different approaches and techniques with feasible development of various biometric applications. We also discuss different classification and clustering techniques to extract all features of faces for identification in real-time applications. We also give all comprehensiveness with critical analysis in calculation of face detection in general implementation. This survey gives traditional methods to automatic face identification formulation to increase the performance in face identification. We also investigate review of implementation in data mining classification, clustering, and feature extraction methods with parameters which consist of face identification such as facial expression, variation, and facial illumination in biometric application developments.

Keywords

Face identification Principal component analysis Independent component analysis Authentication facial databases and industrial neural networks 

References

  1. 1.
    Rautaray, S.S., Agrawal, A.: Real time multiple hand gesture recognition system for human computer interaction. Int. J. Intell. Syst. Appl. 5, 56–64 (2012).  https://doi.org/10.5815/ijisa.2012.05.08CrossRefGoogle Scholar
  2. 2.
    Song, F., et al.: A multiple maximum scatter difference discriminant criterion for facial feature extraction. IEEE Trans. Syst. Man Cybern. Part B Cybern. 37(6), 1599–1606 (2007)Google Scholar
  3. 3.
    Ravi, S., Nayeem, S.: A study on face recognition technique based on Eigenface. Int. J. Appl. Inf. Syst. (IJAIS), 5(4) (2013). ISSN: 2249-0868 (Foundation of Computer Science FCS, New York, USA)Google Scholar
  4. 4.
    Al-Ghamdi, B.A.S., Allaam, S.R., Soomro, S.: Recognition of human face by face recognition system using 3D. J. Inf. Commun. Technol. 4, 27–34Google Scholar
  5. 5.
    Rath, S.K., Rautaray, S.S.: A survey on face detection and recognition techniques in different application domain. Int. J. Mod. Educ. Comput. Sci. 8, 34–44 (2014) (Published Online August 2014 in MECS)Google Scholar
  6. 6.
    Jafri, Rabia, Arabnia, Hamid R.: A survey of face recognition techniques. JIPS 5(2), 41–68 (2009)Google Scholar
  7. 7.
    Viola, Paul, Jones, Michael J.: Robust real-time face detection. Int. J. Comput. Vis. 57(2), 137–154 (2004)CrossRefGoogle Scholar
  8. 8.
    Zhang, C., Zhang, Z.: A survey of recent advances in face detection. Technical report, Microsoft Research (2010)Google Scholar
  9. 9.
    Bowyer, Kevin W., Chang, Kyong, Flynn, Patrick: A survey of approaches and challenges in 3D and multimodal 3D + 2D face recognition. Comput. Vis. Image Underst. 101(1), 1–15 (2006)CrossRefGoogle Scholar
  10. 10.
    Xiaoguang, L.: Image analysis for face recognition. Personal notes, 5 May 2003Google Scholar
  11. 11.
    Zhao, W., et al.: Face recognition: a literature survey. ACM Comput. Surv. (CSUR) 35(4) 399–458 (2003)CrossRefGoogle Scholar
  12. 12.
    Abate, A.F., et al.: 2D and 3D face recognition: a survey. Pattern Recognit. Lett. 28(14) 1885–1906 (2007)CrossRefGoogle Scholar
  13. 13.
    Colombo, Alessandro, Cusano, Claudio, Schettini, Raimondo: 3D face detection using curvature analysis. Pattern Recognit. 39(3), 444–455 (2006)CrossRefGoogle Scholar
  14. 14.
    Bhele1, S.G., Mankar, V.H.: A review paper on face recognition techniques. Int. J. Adv. Res. Comput. Eng. Technol. (IJARCET) 1(8) (2012)Google Scholar
  15. 15.
    Scheenstra, A., Ruifrok, A., Veltkamp, R.C.: A survey of 3D face recognition methods. In: Audio-and Video-Based Biometric Person Authentication. Springer Berlin Heidelberg (2005)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceKrishna UniversityMachilipatnamIndia

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