Abstract

It is a challenging issue how to improve the accuracy of image matching in computer vision. To address this issue, an image matching method is proposed, which is via progressive priors of a putative dataset. Distance ratio priors of a putative dataset are initially employed to calculate a tentative deformation through geometric constraints. Progressive priors of the putative dataset, obtained by the tentative deformation, are then engaged to improve the accuracy of image matching by estimating a global deformation. The comparison experiments illustrate that our proposed method more effectively enhances the accuracy of image matching than six state-of-the-art methods.