LBPH-based Enhanced Real-Time Face Recognition

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).

Authors and Affiliations

Farah Deeba, Hira Memon, Fayaz Ali Dharejo, Aftab Ahmed, Abddul Ghaffar

Keywords

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  • EP ID EP578387
  • DOI 10.14569/IJACSA.2019.0100535
  • Views 96
  • Downloads 0

How To Cite

Farah Deeba, Hira Memon, Fayaz Ali Dharejo, Aftab Ahmed, Abddul Ghaffar (2019). LBPH-based Enhanced Real-Time Face Recognition. International Journal of Advanced Computer Science & Applications, 10(5), 274-280. https://europub.co.uk/articles/-A-578387