Open AccessHuman Face Recognition using LBPH
Author(s) -
Stitiprajna Panda*,
Swati Sucharita Barik,
Sasmita Kumari Nayak,
Aeisuriya Tripathy,
Gourav Mohapatra
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.f8117.038620
Subject(s) - computer science , facial recognition system , artificial intelligence , face detection , biometrics , three dimensional face recognition , computer vision , local binary patterns , object class detection , histogram , haar like features , face recognition grand challenge , face (sociological concept) , pattern recognition (psychology) , image (mathematics) , social science , sociology
During the beginning of seventieth centuries, human facial recognition has become one among the researched areas in the area of finger print scanning and computer vision. Identifying a person with an image has been popularized through the mass media. The recent technologies are totally focusing on developing the smart systems that will recognize the faces for biometric purposes. In this context automatic face recognition is applied for security purposes to find the criminal, attendance system, scientific laboratories etc. This research paper presents the frame work for real time face detection. However, it is less robust to finger print or retina scanning. This paper describes about the face detection and recognition. These technologies are available in the Open-Computer-Vision (OpenCV) library and methodology to implement them using Python in image processing and machine learning. For face detection, Haar-Cascades algorithms were used and for face recognition the algorithm like Eigen faces, and Local binary pattern histograms were used.