Finding point correspondence using local similarity and global constraint under insignificant scaling and roll

Abstract

Establishing point correspondences is an important research topic in computer vision. Proposed is an algorithm using local similarity and global constraint to obtain point correspondence. The point correspondences are obtained by comparing their associated colour codes, which are computed by image gradients, and using spatial relationships among neighbouring feature points. The approach assumes insignificant scaling and roll, and is suitable for real-time applications.