Application Of Local Binary Pattern And Principal Component Analysis For Face Recognition
Recognizing facial expressions of human beings by a computer is an interesting and challenging problem. Facial
feature extraction consists in localizing the most characteristic face components such as eyes, nose, and mouth regions
within the face images that portray the human faces. In this paper, combination of Local Binary Pattern (LBP) and Principal
Component Analysis (PCA) is presented. LBP code is used as texture descriptor of the face image.LBP is used for their
tolerance against different facial expressions, different lighting conditions. The eyes and nose region is extracted from the
LBP face image. PCA is used for dimension reduction of the feature vector.The complete system has been tested on the
standard Olivetti Research Laboratory (ORL) databasesof people under different facial expressions.