Mobile Face Recognition Application using Eigen face Approaches for Android

Authors

  • mais mohamed husein Computer Science Department Mustansiriyah University
  • Dhia Alzubaydi Computer Science Department Mustansiriyah University

DOI:

https://doi.org/10.23851/mjs.v30i1.540

Keywords:

Eigen face, Cascade classifier.

Abstract

Face recognition is one of current biometrics identification methods, that based on the measuring to one of human biological characteristics and utilize them to recognize individuals. these characteristics which are called biometric they are hard to fake because they identify a person by measuring one of its biological characteristics such as (finger print, iris print and face print). With the rapid improvement of mobile technologies that happen in last decade face recognition process can make using mobile phone, this paper explains the building of mobile face recognition system using Eigen face approach, Experimental results have been tested on a local data-set that has been created to analyze the efficiency of the application in various cases including different illumination conditions, variation of view, and orientation, the recognition rate of the application when testing on Galaxy Grand Prime + was 78.4. while The recognition rate when testing on Galaxy Note 5 was 82.4. The accuracy of this application can reach to 100% if we use camera with high accuracy and on good light condition.

References

Jafri, R., and Arabnia, H. R. A survey of face recognition techniques. Journal of Information Processing Systems 5, 2 (2009), 41 – 68.

Anil K. Jain, Patrick Flynn and Arun A. Ross, "Handbook of Biometrics" Springer, in 2007.

W. W. Bledsoe, “The model method in facial recognition,” Panoramic Research Inc., Palo Alto, CA, Rep. PRI:15, Aug. 1966.

M. Turk and A. Pentland, “Eigenfaces for Recognition”, Journal of Cognitive Neuro- science, March 1991.

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Published

2019-08-15

How to Cite

[1]
mais mohamed husein and D. Alzubaydi, “Mobile Face Recognition Application using Eigen face Approaches for Android”, MJS, vol. 30, no. 1, pp. 119–124, Aug. 2019.

Issue

Section

Computer Science