Face Detection E-Attendence System

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-27 Number-3
Year of Publication : 2015
Authors : Prof .T Venkat Narayana Rao, D Vishal Reddy, Rutwik V Jangam
  10.14445/22312803/IJCTT-V27P127

MLA

Prof .T Venkat Narayana Rao, D Vishal Reddy, Rutwik V Jangam "Face Detection E-Attendence System". International Journal of Computer Trends and Technology (IJCTT) V27(3):152-155, September 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
The issue of taking attendance each and every period by the teacher is very time consuming and tiring as well. Therefore we intend to design an application for Android Smart Phones which helps in capturing the image of all the students in the class and then marks the attendance accordingly to their respective faces if present. The image processing will internally be done by the application so as to detect the faces of the students by computing the various features of the face. By introducing this application we intend to reduce the pressure of teachers taking the attendance and saving time as well. The probability that there would be wrong attendance marked for students would also be reduced to a larger extinct as the application completely depends on the face detection of that particular student only. This paper deals with an application that uses face detection and recognition to mark the attendance of the student. Local Binary Pattern Histogram algorithm is used in this approach.

References
[1] Sujata G. Bhele1 and V. H. Mankar2,A Review Paper on Face Recognition Technique ,May 2007 .
[2] T. Ahonen, A. Hadid, M. Peitikainen, Face recognition with local binary patterns. “In Proc. of European Conference of Computer Vision”, 2004.
[3] Faizan Ahmad, Aaima Najam and Zeeshan Ahmed, Image-- based Face Detection and Recognition: “State of the Art”, IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 6, No 1, November 2012.
[4] Lu, Xiaoguang. “Image Analysis for Face Recognition.” Personal notes, Dept. of Computer Science &. Engineering, Michigan State University,, May 2003.
[5] Hassan A. Kingravi,Face Recognition Using Laplacianfaces ,IEEE Trans PAMI, 2005.
[6] Mrs. Sunita Roy and Mr. Susanta Podder, Face Detection and Its Applications, IJREAT International Journal of Research in Engineering & Advanced Technology, Volume 1, Issue 2, April- May, 2013.
[7] K. SRILAKSHMI, M. Z. LAZARUS, SANDEEP. V. M ,Face Recognition Using Laplacian Faces, International Journal on Recent and Innovation Trends in Computing and Communication ,Volume: 1 Issue: 3 ,Mar 2013.
[8] Bonsor, K. "How Facial Recognition Systems Work". Retrieved 2008-06-02.
[9] Pentland, A.; Choudhury, T. “Face recognition for smart environments “, Computer, Volume: 33 Issue: 2, Feb. 2000. [10] Zdeneˇk R íhaVáclav Matyáš “Biometric Authentication Systems ”, FI MU Report Series, November 2000.
[11] Roberto Brunelli and Tomaso Poggio. Face Recognition: Features versus Templates. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(10):1042–1052, October 1993.
[12] RamaChellappa,CharlesL.Wilson,andSaadSirohey. HumanandMachineRecognition of Faces: A Survey. Proceedings of the IEEE, 83(5):705–740, May 1995.
[13] Chin-Seng Chua, Feng Han, and Yeong-Khing Ho. 3D Human Face Recognition using Point Signature. In International Conference on Face and Gesture Recognition, 2000.
[14] ] Ming-Hsuan Yang, “Kernel eigenfaces vs. kernel fisherfaces: Face recognition using kernel methods,” inProc. IEEE International Conference on Automatic Face and Gesture Recognition, Washington D. C., May 2002.
[15] Ming-Hsuan Yang, “Face recognition using extended isomap,” in Proc. IEEE International Conference on Image Processing, Rochester, New York, Sep. 2002, vol. 2.
[16] T. Vetter and T. Poggio, “Face recognition by elastic bunch graph matching,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 733–742, 1997 .
[17] M. Turk and A. Pentland, “Eigenfaces for recognition,” Journal of Cognitive Neuroscience, vol. 3, no. 1, pp. 71–86, Mar. 1991.
[18] Vinita Phatnani,Akash Wanjari, Facial Expression Recognition using Analytical Hierarchy Process, International Journal of Computer Trends and Technology(IJCTT),volume 24 numbr 2,june 2015.

Keywords
Face Detection, Face Recognition, Android, Local Binary Pattern Histogram, LPBH, Attendance, Image Capturing and Processing.