A Comparative Analysis On Various Face Recognition Techniques

Face is an important characteristic part of the human body. What we feel, the various situations we are going through, all are reflected by the human face. Humans are phenomenally have excellent power in recognizing faces. In nut shell, face plays a major role in conveying identity and emotions. So it is important to identify and extract the facial land marks that automatically lead to face recognition. Facial land marking involves the detection and localization of various primary and secondary fucidicial points, may be located at corners or midpoints of the facial components such as eyes, lips etc which are used in face recognition. It is the vital step that ranges from commercial, biometric applications to understanding ones mind's state. But this task has become more challenging and it becomes tough to recognize faces due to various external and the internal factors such as ageing, variations in poses, emotions variations, uncontrolled environmental conditions etc. Thus, to tackle with these conditions and to achieve the purpose of face detection or recognition, it is necessary to make the comparative analysis of various techniques. There are various techniques which have been developed and used. Each technique has its own characteristics, advantages, disadvantages, performance, representative work etc. In this paper, we have present the comparative study of various techniques such as face recognition using PCA, DCT transform, LDA, neural networks, etc. Various parameters, including merits and demerits of all the techniques are taken into account to decide which technique is more useful in future.