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A Comparative Statement for the Facial Recognition Algorithm Via Eigenfaces and the Local Binary Patterns Histograms Algorithm

Chen Wang*

Xi'an Jiaotong University, China.

Periodicity:April - June'2021
DOI : https://doi.org/10.26634/jse.15.4.18429

Abstract

Face recognition systems are based on the premise that each individual has a distinct facial structure, and that by using facial symmetry, it is feasible to do computerized face matching. Since the 1960s, researchers have been working on facial recognition technology, and the results of their efforts are being utilised for security purposes in a variety of organisations and businesses all over the globe. There are a variety of algorithms available for face recognition. This article, which aims to analyze two of the face recognition method, will compare Eigenfaces and Local Binary Patterns Histogram (LBPH). Summing up the research, the accuracy of the Local Binary Patterns Histogram is higher than that of Eigenfaces, and the error rate is lower than that of Eigenfaces.

Keywords

Facial Recognition, Eigenfaces, Local Binary Patterns Histogram (LBPH), Euclidean Distance.

How to Cite this Article?

Wang, C. (2021). A Comparative Statement for the Facial Recognition Algorithm Via Eigenfaces and the Local Binary Patterns Histograms Algorithm. i-manager's Journal on Software Engineering, 15(4), 1-7. https://doi.org/10.26634/jse.15.4.18429

References

[1]. Ali, A. A., Abd El-Hafeez, T., & Mohany, Y. K. (2018). A Robust and efficient system to detect human faces based on facial features. Asian Journal of Research in Computer Science, 2(4), 1-12.

[2]. Ali, A. A., Abd El-Hafeez, T., & Mohany, Y. K. (2019). An accurate system for face detection and recognition. Journal of Advances in Mathematics and Computer Science, 1-19.

[3]. Bilaniuk, O., Fazl-Ersi, E., Laganiere, R., Xu, C., Laroche, D., & Moulder, C. (2014). Fast LBP face detection on lowpower SIMD architectures. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, (pp. 616-622).

[4]. Chehrehgosha, A., & Emadi, M. (2016). Face detection using fusion of LBP and AdaBoost. Journal of Soft Computing and Applications, 2016(1), 1-10.

[5]. Karunarathne, B. A. S. S., Wickramaarachchi, W. H. C., & De Silva, K. K. K. M. C. (2019). Face detection and recognition for security system using Local Binary Patterns (LBP). Journal of ICT, Design, Engineering and Technological Science, 15-19.

[6]. Kshirsagar, V. P., Baviskar, M. R., & Gaikwad, M. E. (2011, March). Face recognition using Eigenfaces. In 2011, 3rd International Conference on Computer Research and Development, (Vol. 2, pp. 302-306). IEEE.

[7]. Patel, R., & Yagnik, S. B. (2013). A literature survey on face recognition techniques. International Journal of Computer Trends and Technology (IJCTT), 5(4), 189-194.

[8]. Phillips, P. J., Moon, H., Rizvi, S. A., & Rauss, P. J. (2000). The FERET evaluation methodology for face-recognition algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(10), 1090-1104.

[9]. Phillips, P. J., Flynn, P. J., Scruggs, T., Bowyer, K. W., Chang, J., Hoffman, K., ... & Worek, W. (2005, June). Overview of the face recognition grand challenge. In 2005, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), (Vol. 1, pp. 947-954). IEEE.

[10]. Samaria, F. S., & Harter, A. C. (1994, December). Parameterisation of a stochastic model for human face identification. In Proceedings of 1994 IEEE Workshop on Applications of Computer Vision, (pp. 138-142). IEEE.

[11]. Symanovich, S. (2021, August 20). What is facial recognition? How facial recognition works. NortonLifeLock.

[12]. Turk, M., & Pentland, A. (1991). Eigenfaces for recognition. Journal of Cognitive Neuroscience, 3(1), 71-86.

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