Face Recognition using Transform Invariant Principal Component Analysis

Face Recognition has becoming the most challenging and interesting area in all applications. It is one of the best biometric techniques. Researchers developed many best face recognition techniques. To overcome this, there should be a technique that exists during the input process to filter the valid image. This paper focuses on the automatic face alignment and ends with enhanced face recognition. This system develops a practical optimization procedure that is effective to simultaneously encode and align a large ensemble of many faces under complex variations and illuminations. This can be achieved through TIPCA algorithm; it extracts and validates the face features automatically.