LBPH-based Enhanced Real-Time Face Recognition

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).

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