Comparison of Feature Detection and Matching Approaches: SIFT and SURF

Feature detection and matching are used in image registration, object tracking, object retrieval etc. There are number of approaches used to detect and matching of features as SIFT(Scale Invariant Feature Transform), SURF(Speeded Up Robust Feature), FAST, ORB etc. SIFT and SURF are most useful approaches to detect and matching of features because of it is invariant to scale, rotate, translation, illumination, and blur. In this paper, there is comparison between SIFT and SURF approaches are discussed. SURF is better than SIFT in rotation invariant, blur and warp transform. SIFT is better than SURF in different scale images. SURF is 3 times faster than SIFT because using of integral image and box filter. SIFT and SURF are good in illumination changes images. Citation: Darshana Mistry, EInfochips Training and Research Academy; Asim Banerjee ,Dhirubhai Ambani Institute of Information and Communication Technology. "Comparison of Feature Detection and Matching Approaches: SIFT and SURF." Global Research and Development Journal For Engineering 24 2017: 7 - 13.