Image Registration Using Feature Points Extraction and Pseudo-Zernike Moments

Abstract

In this paper a new image registration algorithm is proposed. Rotation, translation, and scaling (RTS) transformations are considered in the registration process. The proposed algorithm consists of three main steps: extraction of feature point using a Harris corner detector, obtaining the correspondence between the features points of the reference and input image based on using pseudo-Zernike moments of neighborhoods centered on feature points, and estimating the transformation parameters mapping the input image to the reference one by applying RANSAC. Experimental results illustrate the proposed algorithm is robust to translation, rotation, and slight scaling.