Improved Face Recognition Method usingPCA.

This paper provides an example of the face recognition using PCA method and effect of Graph Based segmentation algorithm on recognition rate. Principle component analysis (PCA) is two or more variabletechniquethatanalyzesafacedatainwhichexperiencearedescribedbyseveralinter-correlateddependentvariables.Thegoalisto extract the important information from the face data, to represent it as a set of new statistically independent variables called principal components. The paper presents a proposed methodology for face recognition based on preprocessing face images using segmentation algorithm and SIFT (Scale Invariant Feature Transform) descriptor. The algorithm has been tested on 50 subjects (100images). The proposed method first waste stedon ESSEX face data base and next on own segmented face data base using SIFT-PCA. The experimental result shows that the segmentation in combination with SIFT-PCA has a positive effect for face recognition and accelerates the recognition PCA technique.