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Skeletons are often used as a framework for part-based shape description and matching. This paper describes some useful strategies that can be employed to improve the performance of such shape matching algorithms. Firstly, it is important that ligature-sensitive information be incorporated into the part decomposition and shape matching processes. Secondly, part decomposition should be treated as a dynamic process in which the selection of the final decomposition of a shape is deferred until the shape matching stage. Thirdly, both local and global measures must be employed when computing shape dissimilarity. Finally, skeletal segments must be weighted by appropriate visual saliency measures during the part matching process. These saliency measures include curvature and ligature-based measures. Experimental results show that the incorporation of these strategies significantly improves shape database retrieval accuracy.