Study and analysis of face recognition system using Principal Component Analysis (PCA)

Face detection and recognition makes possible to use the images of a person face to authenticate him which allows to perform criminal identification, passport verification etc and makes secure system. Principal Component Analysis (PCA) is used to do Face Detection. Here, collection of Eigen face is considered as the face space. Face space helps to encodes best variation presents among given known images of face. In this particular algorithm, in the beginning video can be segmented by method “Shot Boundary Detection”. This technique specifically provides or detects both gradual shot transitions and the cut presents in video. Haar Wavelet Transform used to detects shot boundary. From given method, Haar wavelet transform image of each frame is correlated for shot detection. Frame Correlation threshold require to set so that shot boundaries easily can be detected. Video segmentation has multiple applications like video annotation, video search, video summarization.