A COMPARATIVE ANALYSIS OF OBJECT RECOGNITION SYSTEM USING SIFT,SURF AND FAST ALGORITHMS

Object recognition has always been an area of interest for various researchers since decades. In this paper an attempt has been made to give a comparison between various techniques of object recognition mainly feature based approaches. In this paper an overview of the Famous and impressive technique by David Lowe, which is Scale Invariant Feature Transform (SIFT) has been given. Another very important technique called Speeded-Up Robust Feature Transform (SURF) has been used to conclude with certain interesting results. FAST is the third technique which has also been discussed in this paper.  SIFT, SURF and FAST algorithms has been implemented on COIL dataset and a comparative analysis of these techniques has been given. The algorithms has been evaluated on two parameters i.e., number of features extracted and the time of execution. It has been seen that SIFT has detected more number of features as compared to SIFT and FAST. But the times of execution taken by SURF is comparatively less than SIFT and SURF