Abstract

Introduction This work describes an approach to finding objects in images based on deformable shape models. Boundary finding in two and three dimensional images is enhanced both by considering the bounding contour or surface as a whole and by using model-based shape information. Boundary finding using only local information has often been frustrated by poor-contrast boundary regions due to occluding and occluded objects, adverse viewing conditions and noise. Imperfect image data can be augmented with the extrinsic information that a geometric shape model provides. In order to exploit model-based information to the fullest extent, it should be incorporated explicitly, specifically, and early in the analysis. In addition, the bounding curve or surface can be profitably considered as a whole, rather than as curve or surface segments, because it tends to result in a more consistent solution overall. These models are best suited for objects whose diversity and irregularity of shape make

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