A Study on Various Techniques for Face Recognition

Face recognition is a process of one to many matching. In these particular phenomena, the user matches one person identity with several database images. Various approaches have been used for the purpose of face recognition. These approaches use different features for face recognition purpose. The feature considered for face recognition are shape, distance between two traits of face, texture features for face. Texture features are particularly susceptible to the resolution of images, when the resolution changes the calculated textures are not accurate. Texture features computed for low resolution face images does not provide better feature information. So, there is a big issue in face recognition for low resolution images. EULBP (Equalized Uniform Local binary Pattern) has been implemented for the problem of low resolution but it does not provide better results up to an extent. In this paper, research is done to improve the accuracy for the low resolution images. By analyzing various approaches for face recognition there is need to develop a new approach which can provide better results using texture features for blurred images.