Abstract

In this paper we present an efficient 2D object recognition method that uses multiscale tree representations. A planar object is represented by means of a tree, in which each node corresponds to a boundary segment at some level of resolution and an arc connects nodes corresponding to segments at successive levels that are spatially related. The problem of matching an object against a model is formulated as the one of determining the best mapping between nodes at all levels of the two associated trees. The proposed matching algorithm is based on dynamic programming and has optimal O(∣T ∣∣T′∣) time complexity, where ∣ T∣ and ∣ T′∣ are the number of nodes in the two trees.

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