Abstract: Facial recognition has always gone through a consistent research area due to its non-modelling nature and its diverse applications. As a result, day-to-day activities are increasingly being carried out electronically rather than in pencil and paper. Today, computer vision is a comprehensive field that deals with a high level of programming by feeding the input images/videos to automatically perform tasks such as detection, recognition and classification. Even with deep learning techniques, they are better than the normal human visual system. In this article, we developed a facial recognition system based on the Local Binary Pattern Histogram (LBPH) method to treat the real-time recognition of the human face in the low and high-level images. We aspire to maximize the variation that is relevant to facial expression and open edges so to sort of encode edges in a very cheap way. These highly successful features are called the Local Binary Pattern Histogram (LBPH).

Farah Deeba, Hira Memon, Fayaz Ali Dharejo, Aftab Ahmed and Abddul Ghaffar, “LBPH-based Enhanced Real-Time Face Recognition” International Journal of Advanced Computer Science and Applications(IJACSA), 10(5), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100535

@article{Deeba2019,
title = {LBPH-based Enhanced Real-Time Face Recognition},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100535},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100535},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {5},
author = {Farah Deeba and Hira Memon and Fayaz Ali Dharejo and Aftab Ahmed and Abddul Ghaffar}
}