Abstract

We present an approach to invariant matching. In this approach, an object or a pattern is invariantly represented by an object-centered description called an attributed relational structure (ARS) embedding invariant properties and relations between the primitives of the pattern such as line segments and points. Noise effect is taken into account such that a scene can consist of noisy sub-parts of a model. The matching is then to find the optimal mapping between the ARSs of the scene and the model. A gain functional is formulated to measure the goodness of fit and is to be maximized by using the relaxation labeling method. Experiments are shown to illustrate the matching algorithm and to demonstrate that the approach is truly invariant to arbitrary translations, rotations, and scale changes under noise. Index terms --- Attributed relational structures, invariance, pattern recognition, relaxation labeling, sub-graph matching. Pattern Recognition, 25(6):583--594, June 1992 2 Contents 1...

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