A skeleton based shape matching and recovery approach

A robust skeleton-based shape matching method for model-based shape recovery applications is presented. The object model consists of both a skeleton model and a contour segments model, which are used in tandem and in a complementary manner. Initially, the skeleton of the contour, provided by a deformable contour method (DCM), is matched against a set of object skeleton models to select a candidate model and determine the corresponding landmarks on the contours. Segments obtained from these landmarks are then matched against the detected model segments for errors. For any large segment mismatch error, a fine-tuning process, which is formulated as a maximization of a posteriori probability, given the contour segments model and image features, is performed for the final result. The skeleton matching algorithm is illustrated by using a set of animal profile examples. Experimental results of shape recovery from practical applications, such as an MR knee image, are very encouraging.