Open AccessLocal Binary Patterns Histograms (LBPH) Based Face Recognition
Author(s) -
Satya Bhushan Verma,
Er. Nidhi Tiwari
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a9483.109119
Subject(s) - histogram , local binary patterns , biometrics , facial recognition system , artificial intelligence , pattern recognition (psychology) , computer science , face (sociological concept) , computer vision , image (mathematics) , social science , sociology
The human face has been broadly used in computer vision field for individual recognition. The face recognition is one of the secure ways to protect the data over the internet. In this paper we use (LBPH) Local Binary Patterns Histogram based Face Recognition. We use Yale face database for experiment and it contains 165 grey images in the GIF format of 15 person and 11 image per person and in this experiment we use only normal image in 180*180 at grey scale images and in this research article in the verification phase the difference between two histograms are calculated by Chi-square distance, Manhattan distance. The proposed technique has achieved TSR=98.8% in Chi-square and TSR=98.5% in Manhattan distance parameter. Person Identification using their physical structure or behavioral characteristic is known as the biometric.