Finding Missing People using Face Recognition

Face recognition using feed forward technique may be an important technique to use in computer innovation by machine learning, bio metrics, pattern recognition, pattern analysis and digital image processing. It is a systematic method for training multi-layer convolution neural network. Now a day’s bio metric is a currant topic for the research community. Bio metric is used for security purpose for its real time applications. Face recognition is one of the challenging issues in bio metrics. These issues in our mind, we are focusing on the face recognition problems. Face recognition must address several difficult problems such as pose, illuminations and expression, background imaged head size, and head orientation. This difficulty arises from the fact that faces must be represented in a way to distinguish a particular face from all other faces. Face recognition system consists of four modules: face detection, face normalization, face feature extraction and matching. The face recognition process is often operated in face verification, face identification and face watch. In face verification a query face image is compared against a template face image whose identify is being claimed. In fact identification a query face image is compared against all templates in the database to determine the claimed identify. In face tracking and surveillance, face images are tracked and compared with stored databases. Our study is focusing on analysis the various face recognition algorithms and investigate to propose the face recognition algorithm with its enhanced performance.