IMPLEMENTATION OF HIGH PERFORMANCE FEATURE EXTRACTION METHOD USING ORIENTED FAST AND ROTATED BRIEF ALGORITHM

Abstract

Feature-based image matching is an important characteristic in many computer based applications such as object recognition, 3D stereo reconstruction, structure-from-motion and images stitching. These applications require a lot real-time performance. Feature based algorithms are well-suited for such operations. Different algorithms are used for image processing like Scaleinvariant feature transform (SIFT), Speeded up Robust Features (SURF), Oriented FAST and Rotated BRIEF (ORB). ORB is one of the fast binary descriptor which is relying on BRIEF, where the BRIEF is rotation invariant and resistant to noise. This paper gives the advantages of rotation invariance and scale invariance of ORB algorithm for object detection technique. Query based object detection method is explained in this paper for object detection with efficient computation time. Different experimental results prove the scale invariance and rotation in variance of ORB in query based object detection method.