Face Recognition using OpenCV

Authors

  • Shivani Duggi Dept. of Computer Science, RYMEC, Ballari, Karnataka. India
  • Khajabani S Dept. of Computer Science, RYMEC, Ballari, Karnataka. India
  • Katha Harshitha Dept. of Computer Science, RYMEC, Ballari, Karnataka. India
  • NB Shaguftha Dept. of Computer Science, RYMEC, Ballari, Karnataka. India
  • M Nagaraj Dept. of Computer Science, RYMEC, Ballari, Karnataka. India

DOI:

https://doi.org/10.26438/ijcse/v8i5.187191

Keywords:

Automatic, Database, Face Recognition, LBPH

Abstract

The rate of computer power steadily doubles every 13 months, with this face detection and recognition has transcended from an esoteric to a popular area of research in computer vision and one of the better and successful applications of image analysis and algorithm based understanding. Because of the intrinsic nature of the problem, computer vision is not only a computer science area of research, but also the object of neuro- scientific and psychological studies, mainly because of the general opinion that advances in computer image processing and understanding research will provide insights into how our brain works and vice-versa. Considering the general curiosity and interest in the matter, we propose to create and develop a facial recognition based attendance management system, using Intel’s open source computer vision project, OpenCV and Microsoft’s .NET framework. The paper describes how to take student’s attendance using face recognition. The face recognition is implemented with the help of Local Binary Patterns Histogram (LBPH) algorithm. The system will recognize the face of the student and saves the response in database automatically.

References

[1] Baron, R.J. “Mechanisms of human facial recognition”,International Journal of Man Machine Studies, 15:137-178, 1981.

[2] Mr. Dipesh Sharma, “A study of various Face Detection methods”.

[3] Xiang-Yu Li (&) and Zhen-Xian Lin, “Face Recognition based on HOG and Fast PAC Algorithm”.

[4] Adam Schmidt, Andrzej Kassinki, “The performance of the Haar Cascade Classifiers Applied to the Face and Eyes Detection”.

[5] Arun Katara, Mr.Sudesh, V.Kolhe, “Attendance System Using Face Recognition and Class Monitoring System”,

[6] Beymer, D. and Poggio, T., “Face Recognition from One Example View”, A.I. Memo No. 1536, C.B.C.L. Paper No. 121. MIT, 1995.

[7] Craw, I., Ellis, H., and Lishman, J.R., “Automatic extraction of face features”, “Pattern Recognition Letters”, 5:183-187, February, 1987.

[8] Goldstein, A.J., Harmon, L.D., and Lesk, A.B. “Identification of human faces”, in Proc. IEEE, Vol. 59, page 748, 1971

[9] de Haan, M., Johnson, M.H. and Maurer D. (1998) Recognition of individual faces and average face prototypes by 1- and 3- month- old infants. Centre for Brain and Cognitive

[10] Heisele, B. and Poggio, T., “Face Detection”, Artificial Intelligence Laboratory, MIT, 1999.

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Published

2020-05-31
CITATION
DOI: 10.26438/ijcse/v8i5.187191
Published: 2020-05-31

How to Cite

[1]
S. Duggi, K. S, K. Harshitha, N. Shaguftha, and M. Nagaraj, “Face Recognition using OpenCV”, Int. J. Comp. Sci. Eng., vol. 8, no. 5, pp. 187–191, May 2020.

Issue

Section

Research Article