LBPH-based enhanced real-time face recognition

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

Research output: Contribution to journalArticlepeer-review

59 Scopus citations

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).

Original languageBritish English
Pages (from-to)274-280
Number of pages7
JournalInternational Journal of Advanced Computer Science and Applications
Volume10
Issue number5
DOIs
StatePublished - 2019

Keywords

  • Face recognition
  • Feature extraction
  • Local Binary Pattern Histogram (LBPH)

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