A new image matching technique is described. It is implemented as an object-independent hierarchical structural
juxtaposition algorithm based on an alphabet of simple object-independent contour structural elements. The structural
matching applied implements an optimized method of walking through a truncated tree of all possible juxtapositions of
two sets of structural elements. The algorithm was initially developed for dealing with 2D images such as the aerospace
photographs, and it turned out to be sufficiently robust and reliable for matching successfully the pictures of natural
landscapes taken in differing seasons from differing aspect angles by differing sensors (the visible optical, IR, and SAR
pictures, as well as the depth maps and geographical vector-type maps). At present (in the reported version), the
algorithm is enhanced based on additional use of information on third spatial coordinates of observed points of object
surfaces. Thus, it is now capable of matching the images of 3D scenes in the tasks of automatic navigation of extremely
low flying unmanned vehicles or autonomous terrestrial robots. The basic principles of 3D structural description and
matching of images are described, and the examples of image matching are presented.
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