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.