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Proceedings Paper

Image Registration Through The Exploitation Of Perspective Invariant Graphs
Author(s): John F. Gilmore
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Paper Abstract

This paper describes two new techniques of image registration as applied to scenes consisting of natural terrain. The first technique is a syntactic pattern recognition approach which combines the spatial relationships of a point pattern with point classifications to accurately perform image registration. In this approach, a preprocessor analyzes each image in order to identify points of interest and to classify these points based on statistical features. A classified graph possessing perspective invariant properties is created and is converted into a classification-based grammar string. A local match analysis is performed and the best global match is con-structed. A probability-of-match metric is computed in order to evaluate match confidence. The second technique described is an isomorphic graph matching approach called Mean Neighbors (MN). A MN graph is constructed from a given point pattern taking into account the elliptical projections of real world scenes onto a two dimensional surface. This approach exploits the spatial relationships of the given points of interest but neglects the point classifications used in syntactic processing. A projective, perspective invariant graph is constructed for both the reference and sensed images and a mapping of the coincidence edges occurs. A probability of match metric is used to evaluate the confidence of the best mapping.

Paper Details

Date Published: 26 October 1983
PDF: 11 pages
Proc. SPIE 0397, Applications of Digital Image Processing V, (26 October 1983); doi: 10.1117/12.935280
Show Author Affiliations
John F. Gilmore, Martin Marietta Orlando Aerospace (United States)


Published in SPIE Proceedings Vol. 0397:
Applications of Digital Image Processing V
Andre J. Oosterlinck; Andrew G. Tescher, Editor(s)

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