Image mosaics based on pseudo-Zernike moments

The traditional feature-based algorithm was found to be sensitive to rotations and noise. In this paper, an automatic image mosaics technique was proposed by using the pseudo-Zernike moments defined on the feature point's neighborhood. Firstly using the Harris corner detector gain the feature points, compute the pseudo-Zernike moments defined on these feature point's neighborhood, through comparing the Euclidean distance of these pseudo-Zernike moments to extract the initial feature points pair, then eliminate spurious feature points pair by geometric transform model obtained from RANSAC method, finally transform the input image with the correct mapping model for image fusion and complete image stitching. Experimental results demonstrate that the proposed algorithm is robust to translation, rotation, noise and slight scaling.