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Geometric registration of visual images is a fundamental intermediate processing step in a wide variety of computer vision applications that deal with image sequence analysis. 2D motion recovery and mosaicing, 3D scene reconstruction and also motion detection approaches strongly rely on accurate registration results. However, automatically assessing the overall quality of a registration is a challenging task. In particular, optimization criteria used in registration are not necessarily closely linked to the final quality of the result and often show a lack of local sensitivity. In this paper we present a new approach for an objective quality metric in 2D image registration. The proposed method is based on local structure analysis and facilitates votingtechniques for error pooling, leading to an objective measure that correlates well with the visual appearance of registered images. Since observed differences are furthermore classified in more detail according to various underlying error sources, the new measure not only yields a suitable base for objective quality assessment, but also opens perspectives towards an automatic and optimally adjusted correction of errors.

TOWARDS OBJECTIVE QUALITY ASSESSMENT OF IMAGE REGISTRATION RESULTS