CFP last date
28 July 2025
Call for Paper
August Edition
IJAIS solicits high quality original research papers for the upcoming August edition of the journal. The last date of research paper submission is 28 July 2025

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Financial Time Series Predictions with a Hybrid BNN-LSTM Approach

Anika Tahsin Biva A.B.M. Shahadat Hossain Md. Shafiul Alom Khan Iqbal Habib
Random Articles
Reseach Article

A Study on Face Recognition Technique based on Eigenface

by S. Ravi, Sadique Nayeem
journal cover thumbnail

International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 5 - Number 4
Year of Publication: 2013
Authors: S. Ravi, Sadique Nayeem
10.5120/ijais12-450902

S. Ravi, Sadique Nayeem . A Study on Face Recognition Technique based on Eigenface. International Journal of Applied Information Systems. 5, 4 ( March 2013), 57-62. DOI=10.5120/ijais12-450902

@article{ 10.5120/ijais12-450902,
author = { S. Ravi, Sadique Nayeem },
title = { A Study on Face Recognition Technique based on Eigenface },
journal = { International Journal of Applied Information Systems },
issue_date = { March 2013 },
volume = { 5 },
number = { 4 },
month = { March },
year = { 2013 },
issn = { 2249-0868 },
pages = { 57-62 },
numpages = {9},
url = { https://www.ijais.org/archives/volume5/number4/440-0902/ },
doi = { 10.5120/ijais12-450902 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T17:58:31.033721+05:30
%A S. Ravi
%A Sadique Nayeem
%T A Study on Face Recognition Technique based on Eigenface
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 5
%N 4
%P 57-62
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Artificial Face Recognition is one of the popular areas of research in Image processing. It is different from other biometric recognition because faces are complex, multidimensional and almost all human faces have a similar construction. Out of many issues some of the most important issues associated with facial recognition are the type, format and composition (different background, variant illumination and different facial expression) of the face images used for the recognition. Different approaches use the specific databases which consist of single type, format and composition of image. Thus, these approaches lack the robustness. So, in this paper an comparative study is made for four different image databases with the help of basic Eigenface PCA face recognition technique.

References
  1. R. Chellappa, C. L. Wilson, and S. Sirohey, 1995, Human and machine recognition of faces: A survey, Proc. of IEEE, volume 83, pages 705-740.
  2. . P. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman, 1997, Eigenfaces vs. fisherfaces: Recognition using class specific linear projection, IEEE Trans. Pattern Analysis and Machine Intelligence, 19(7):711-720.
  3. . A. S. Georghiades, D. J. Kriegman, and P. N. Belhumeur, 1998, Illumination cones for recognition under variable lighting: Faces, Proc. IEEE Conf. on Computer Vision and Pattern Recognition, pages 52-59.
  4. S. A. Sirohey, 1993, Human face segmentation and identification, Technical Report CAR-TR-695, Center for Automation Research, University of Maryland, College Park, MD.
  5. M. Turk and A. Pentland, 1991, Eigenfaces for recognition, Journal of Cognitive Neuroscience, vol. 3, No. 1
  6. Sirovich, L. and Kirby M. , Low dimensional procedure for the characterization of human faces, Journal of the Optical Society of America A, 4(3), 519-524.
  7. A. Samal and P. A. Iyengar, 1992, Automatic recognition and analysis of human faces and facial expressions: A survey, Pattern Recognition, 25(1): 65-77.
  8. Athinodoros S. Georghiades, David J. Kriegman and Peter N. Belhumeur, Illumination cones for recognition under variable lighting: Faces, Center for Computational Vision and Control.
  9. Caifeng Shan, Shaogang Gong, Peter W. McOwan, 2009, Facial expression recognition based on Local Binary Patterns: A Comparative Study, Image and Vision Computing 27, 803-816.
  10. A. Pentland and T. Choudhury, Feb. 2000, Face recognition for smart environments, Computer, Vol. 33 Iss. 2.
  11. Essex face database -face94, University of Essex, UK, http://cswww. essex. ac. uk/mv/allfaces/index. html
  12. Vidit Jain, Amitabha Mukherjee, 2002, The Indian Face Database, http://vis-www. cs. umass. edu/~vidit/IndianFaceDatabase/
  13. Yale Database, http://cvc. yale. edu/projects/yalefaces/yalefaces. html
  14. FACE 1999, http://www. vision. caltech. edu/html-files/archive. html
  15. ORL Database, http://www. cl. cam. ac. uk/research/dtg/attarchive/facedatabase. html
  16. AR database, http://rvl1. ecn. purdue. edu/~aleix/aleix_face_DB. html
  17. UMIST Face Database, http://www. sheffield. ac. uk/eee/research/iel/research/face
Index Terms

Computer Science
Information Sciences

Keywords

Principal Component Analysis (PCA) Eigenface

Powered by PhDFocusTM