Abstract
A review is presented of the use of hierarchical data structures for the representation of shape. The presentation is primarily in terms of variants of a spatial data structure known as a quadtree. These data structures are based on a recursive decomposition of the interior of the shape or on its boundary. The focus is on the representation of two-dimensional shape used in applications in image processing and computer vision. The adaptation of the concepts of a distance, a skeleton, and a medial axis transform to a shape represented by a quadtree is described, as is a region expansion (i.e., image dilation) algorithm that executes in time independent of the radius of expansion.
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