Image matching with SIFT feature
Rajkumar N. Satare, S. R. Khot · 2018 2nd International Conference on Inventive Systems and Control (ICISC) · 2018
An image matching algorithm is present in this paper. A set of interest points known as SIFT features are computed for a pair of images. Every keypoint has a descriptor based on histogram of magnitude and direction of gradients. These descriptors are the primary input for the image correspondence algorithm. Initial probabilities are assigned for categories considering a feature point assignment to one of the category as a classification problem. For selecting the neighbours for the left keypoint, a fixed number of pixels around the keypoint, considered as a window, are selected. The neighbours of the right keypoint are based on inspection of pair of images and the disparity range. The probabilistic estimates are iteratively improved by a relaxation labeling technique. The neighbour keypoints which will contribute to improve the probability is based on consistency property.