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Face Recognition Techniques for Authentication in Smart Devices - Comparative Study

by Jerin George, Tulasi B.
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International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 12 - Number 1
Year of Publication: 2017
Authors: Jerin George, Tulasi B.
10.5120/ijais2017451671

Jerin George, Tulasi B. . Face Recognition Techniques for Authentication in Smart Devices - Comparative Study. International Journal of Applied Information Systems. 12, 1 ( Apr 2017), 33-37. DOI=10.5120/ijais2017451671

@article{ 10.5120/ijais2017451671,
author = { Jerin George, Tulasi B. },
title = { Face Recognition Techniques for Authentication in Smart Devices - Comparative Study },
journal = { International Journal of Applied Information Systems },
issue_date = { Apr 2017 },
volume = { 12 },
number = { 1 },
month = { Apr },
year = { 2017 },
issn = { 2249-0868 },
pages = { 33-37 },
numpages = {9},
url = { https://www.ijais.org/archives/volume12/number1/981-2017451671/ },
doi = { 10.5120/ijais2017451671 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T19:07:52.967085+05:30
%A Jerin George
%A Tulasi B.
%T Face Recognition Techniques for Authentication in Smart Devices - Comparative Study
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 12
%N 1
%P 33-37
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

With rapid development of technology there has been a surge in hand-held devices. These devices are looked upon as an alternative to the traditional devices like personal computer and laptop. As the storage and the processing capabilities of these devices are increasing they are been termed as smart devices. The amount of personal data stored in these devices has increased many folds. In order to ensure that the critical data that is stored in these devices is secured, it is essential to put in place authentication processes. Authentication can be done at multiple levels, ranging from a password to face recognition. Algorithms like Eigenfaces, Fisherfaces are being used as a part of authentication applications. This paper tries to provide a comparative study on most commonly used face recognition algorithms.

References
  1. Aberdeen Database, Web address: http://pics.stir.ac.uk/2D_face_sets.htm/, November 2016.
  2. G. Hemalatha and C. P. Sumathi, “A Study of Techniques for Facial Detection and Expression Classification”, International Journal of Computer Science and Engineering Survey (IJCSES), Volume 5, No. 2, April 2014.
  3. Japanese Female Facial Expression (JAFFE) Database, Web address: http://www.kasrl.org/jaffe.html/, November 2016.
  4. Jigar M. Pandya, DevangRathod and Jigna J. Jadav, “A Survey of Face Recognition approach”, International Journal of Engineering Research and Applications (IJERA), Volume 3, Issue 1, January – February 2013.
  5. Mandeep Kaur, Rajeev Vashisht and NirvairNeeru, “Recognition of Facial Expressions with Principal Component Analysis and Singular Value Decomposition”, International Journal of Computer Applications, Volume 9, No. 12, November 2010.
  6. MarijetaSlavkovic and DubravkaJevtic, “Face Recognition Using Eigenface Approach”, Serbian Journal of Electric Engineering, Vol. 9, No.1, February 2012.
  7. Matthew Turk and Alex Pentland, “Eigenfaces for Recognition”, Journal of Cognitive Neuroscience, Vol. 3, No. 1, 1991.
  8. NaotoshiSeo, “Eigenfaces and Fisherfaces, 2006.
  9. Peter N. Belhumeur, Joao P. Hespanha and David J. Kriegman, “Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection”, IEEE Trans. on PAMI, July 1997.
  10. RajibSaha and DebotoshBhattacharjee, “Memory Efficient Human Face Recognition Using Fiducial Points”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume2, Issue 1, January 2012.
  11. Satish Palaniappan, Naveen Hariharan, Naren T. Kesh, Vidhyalakshimi and Angel Deborah S., “Home Automation Systems- A study”, 2015.
  12. Shiwani, Dr. Kamal Sharma and Er. Gurinder Singh, “PCA Based Improved Algorithm for Face Recognition”, International Journal of Recent Research Aspects, February 2015.
  13. SomayyaMadakam, R. Ramaswamy and SiddharthTripathi, “Internet of Things [IoT]: A Literature Review”, Journal of Computer and Communications, Web address: http://www.scirp.org/journal/jcc http://dx.doi.org/10.4236/jcc.2015.35021/, 2015, 3, 164-173, Published Online May 2015 in SciRes.
  14. Stefano Arca, Paola Campadelli and RaffaellaLanzarotti, “A Face Recognition System Based on Local Feature Analysis”, Springer-Verlag Berlin Heidelberg, 2003.
  15. Stefano Arca, Paola Campadelli and RaffaellaLanzarotti, “An Automatic Feature-Based Face Recognition System”, Web address: http://www.researchgate.net/publication/4035716/, October 2003.
  16. W. Zhao, R. Chellappa, A. Rosenfeld and P. J. Phillips, “Face Recognition: A Literature Survey”, ACM Computing Surveys, 2003.
  17. Yalefaces Database, Web address: http://cvc.cs.yale.edu/cvc/projects/yalefaces/yalefaces.html/, November 2016.
  18. Yi-Shin Liu, Wai-Seng Ng and Chun-Wei Liu, “A Comparison of Different Face Recognition Algorithms”, 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Correlation Eigenfaces Face Recognition Fisherfaces Lambertian Surface MATLAB Principal Components Analysis Smart Devices

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