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In this paper, an approach is described for recognizing and locating partially hidden objects in an image. The method is based upon matching pairs of boundary segments of the template of an object with pairs of boundary segments in the image. Using a Bayesian based signal detection approach, pairs of segments are selected from the template of the object such that the probability of correctly identifying the object given that the pair is matched in the image is close to one. Assuming that models of all objects which might appear in the scene (a reasonable assumption for industrial applications) are known a priori, suitable pairs of segments can be determined a priori. Preliminary investigation suggests that the technique is robust and that subsecond recognition time can be achieved.