International Journal of Modern Computation, Information and Communication Technology

ISSN 2581-5954

July 2018, Vol. 1, Issue 2, pp. 45-50.​​

Automated Attendance Management by Facial Recognition Using Histogram     
M. Gayathri, S. Jothi, A. Chandrasekar*
Department of Computer Science and Engineering, St. Joseph’s College of Engineering, Chennai - 600119. India.
*Corresponding author’s e-mail:      


Face recognition is the identification of humans by the unique characteristics of their Faces. Face recognition technology is the least intrusive and fastest growing technology and also proves to be the easier tool for certain works. It works with the most obvious individual identifier the human face .This research aims at providing a system to automatically record the students’ attendance during lecture hours in a hall or room using facial recognition technology instead of the traditional manual methods. The objective behind this research is to thoroughly study the field of facial recognition by image processing which is very important and is used in various applications like identification and detection. This system is been implemented with 4 modules namely Image Capturing, Segmentation of group photo (Face Detection), Face comparison (Recognition), Updating of Attendance in database.

Keywords: Histogram; Haar Cascade; Face detection; Face Comparison.


  1. ​Shehu V, Dika A. Using real time computer vision algorithms in automatic attendance management systems. 32nd Int. Conf. on Information Technology Interfaces. June 21-24, 2010.
  2. Jawale JB. Ear Based attendance monitoring system. Proceedings of International Conference on Emerging Trends in Electrical and Computer Technology. March 23-24, 2011. 
  3. Krishnan MG, Balaji, Shyam Babu, Implementation of automated attendance system using face recognition. International Journal of Scientific and Engineering Research 2015;6:30-3.
  4. Shirodkar M, Sinha V, Jain U, Nemade B. Automated attendance management system using face recognition. International Journal of Computer Applications 2015;2:23-8.
  5. Thakare N, Shrivastava M, Kumari N, Kumari N, Kaur D, Singh S. Face Detection and recognition for automatic attendance system. International Journal of Computer Science and Mobile Computing 2016;5:74-8.
  6. Shriwastav S, Jain DC. A Review on face recognition attendance system. International Journal of Computer Applications 2016;143:19-22.
  7. Wang NJ. A Real-time Multi-face Detection System Implemented on FPGA. IEEE International Symposium on Intelligent Signal Processing and Communication Systems. November 4-7, 2012.
  8. Lukas S, Mitra AR, Desanti RI, Krisnadi D. Student attendance system in classroom using face recognition technique. International Conference on Information and Communication Technology Convergence. October 19-21, 2016.
  9. Kar N, Debbarma MN, Saha A, Pal DR. Study of implementing automated attendance system using face recognition technique. International Journal of Computer and Communication Engineering 2012;1(2):100-3.