This paper investigates a new face recognition system based on an efficient design of classifier using SIFT (Scale

Invariant Feature Transform) feature keypoint. This proposed system takes the advantage of SIFT feature which possess strong

robustness to the expression, accessory, pose and illumination

variations. One MLP (Multi Layer Perceptron) based network is

adopted as classifier of SIFT keypoint feature. The proposed

classifier classifies each keypoint into face ID then an ID index histogram counting method is applied as the identification method to recognize face images. Also a bootstrapping method is investigated to select training images during training MLP. The performance of face recognition in some challenging databases is improved efficiently.