Image matching via progressive priors

Abstract

It is a fundamental and 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 antecedents of a presumptive dataset are initially employed to calculate a tentative deformation through geometric constraints. Progressive priors of the presumptive 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.