AUTOMATIC EXAM ATTENDANCE SYSTEM BASED ON ILLUMINATION INVARIANT FACE RECOGNITION

Abstract

Security systems are used in several ways. In the developing technology, the computer systems are employed to solve different kinds of problems whereas they can be also used for security purposes. Application of the computer-aided security systems are one of the applicable technologies today especially in the crowded places such as entrance gates where high security measure is requested. On the other hand, automatic face recognition is useful in the applications where the recognition of the authorized people should be completed in a limited time. An application, that is the identification of the students for exam security is one of the important issues in universities where crowded exams take place. Unidentified people other than one's own examinations can be defined as problematic in terms of exam assessment. The paper proposes a new automatic class attendance system based on illumination invariant face recognition. System consists of three stages which are the face detection, facial feature extraction and classification. A known method will be employed for face detection part. For the facial feature extraction stage, non-subsampled Contourlet transform is used. The classification is done by the use of a known method which is the correlation coefficient. The system is currently under test and expected to run at acceptable recognition rates to be used in an automatic class attendance system.

Keywords

• Automatic attendance,face recognition,non-subsampled contourlet transform (NSCT),exam security,student authorization

References

1. M.N. Do and M. Vetterli (2005). The contourlet transform: an efficient directional multiresolution image representation. Image Processing, IEEE Transactions on, 14(12):2091–2106. A.L. da Cunha, Jianping Zhou, and M.N. Do (2006). The nonsubsampled contourlet transform: Theory, design, and applications. Image Processing, IEEE Transactions on, 15(10):3089–3101, oct. 2006. N.Kar, M.N.Debbarma, A.Saha and D.R.Pal (2012). Study of implementing automated attendance system using face recognition technique. International Journal of Computer and Communication Engineering, Vol.1, No.2, July 2012. A.Patil and M.Shukla (2014). Implementation of classroom attendance system based on face recognition in class. International Journal of Advances in Engineering and Technology, Vol.7, Issue 3, pp.974-979. Viola P., Jones J. (2004). Robust real time face detection. International Journal of Computer Vision, 57(2), pp.137-154. Y. Cheng, C.L. Wang, Z.Y. Li, Y.K. Hou, and C.X. Zhao (2010). Multiscale principal contour direction for varying lighting face recognition. Electronics Letters, 46(10):680–682, 13. H. Soyel, B.Ozmen and P.McOwan (2012). Illumination robust face representation based on intrinsic geometrical information. IET Conference on Image Processing (IPR 2012), e-ISBN: 978-1-84919-632-1, DOI: 10.1049/cp.2012.0437. Yin, L. Wei, X. Sun, Y. Wang, J., Rosato, M. (2006). A 3d facial expression database for facial behavior research. In Proceedings of International Conferance on FGR, pp. 211-216, UK. D.D.-Y. Po and M.N. Do. (2006). Directional multiscale modelling of images using the contourlet transform. Image Processing, IEEE Transactions on, 15(6):1610–1620, June 2006.