Local Binary Patterns Histograms (LBPH) Based Face Recognition
Satya Bhushan Verma1, Nidhi Tiwari2

1Dr. Satya Bhushan Verma*, Department of Computer Science, BBA University, Lucknow, India.
2Er. Nidhi Tiwari, Computer Science & Engineering, Dr A.P.J. Abdul Kalam Technical University Lucknow, India.
Manuscript received on September 20, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 1088-1091 | Volume-9 Issue-1, October 2019 | Retrieval Number: A9483109119/2019©BEIESP | DOI: 10.35940/ijeat.A9483.109119
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: 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.
Keywords: Biometric, Face recognition, LBPH, Gabor filter.