Partial shape recognition as an optimization problem

Abstract Recognition of shapes which are incomplete or distorted is important in many image analysis applications. Varying background conditions, lighting, clouds, or physical obstructions may prevent observation of an entire object. Segmentation techniques may also render distorted contours. Global shape recognition techniques perform poorly in these situations, since a change in one portion of the shape will affect all of the features. Partial shape recognition techniques will be described in which a contour is represented as a sequence of local features derived from segments of the entire contour. The recognition problem will be posed as a combinatorial optimization problem, in which the best sequence of matching known and unknown contour segments is desired. Solutions to this matching problem using dynamic programming and simulated annealing will be discussed. Another more heuristic approach using a Best First Search will also be described. Experimental results will be presented and discussed.

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