Comparative study on SIFT and SURF face feature descriptors

Abstract

Feature refers to some relevant information which is present on images or faces. Feature extraction used to extract those features from the face. Among that bulk of keypoints, only robust features are detected by using feature descriptors. This paper analyzes 2 robust feature detector and descriptors are: Scale-Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF). These two robust feature descriptors are invariant to scale changes, blur, rotation, illumination changes and affine transformation. SIFT is an algorithm used to extract the features from the images. SURF is an efficient algorithm is same as SIFT performance and reduced in computational complexity. SIFT algorithm presents its ability in most of the situation but still its performance is slow. SURF algorithm is same as SIFT with fastest one and good performance.