The Face recognition and image or video
recognition are popular research topics in biometric
technology. Real-time face recognition is an exciting field
and a rapidly evolving issue. Key component analysis
(PCA) may be a statistical technique collectively called
correlational analysis . The goal of PCA is to scale back the
massive amount of knowledge storage to the dimensions of
the functional space required to render the face
recognition system. The wide one-dimensional pixel vector
generated from the two-dimensional image of the face and
therefore the basic elements of the spatial function are
designed for face recognition using PCA. this is often the
projection of your own space. Sufficient space is decided
by the brand. specialise in the eigenvectors of the
covariance matrix of the fingerprint image collection. i'm
building a camera-based real-time face recognition system
and installing an algorithm. Use OpenCV, Haar Cascade,
Eigen face, Fisher Face, LBPH and Python for program
development.
Efficient Information-Theoretic-Statistical (ITSM) Equation for Face Recognition Technique: Comparison with Statistical Technique and Information-Theoretic Technique
