Abstract
The quadtree is a hierarchical data structure used for the compact representation of two-dimensional images. It has the advantages of data compression and fast execution of certain feature computations. However, the quadtree representation of an object is heavily affected by its location, orientation, and relative size. If the image of an object is normalized with respect to its centroid and principal axes, and scaled to a standard size, then its quadtree representation is invariant to rotation, translation, and size change. In addition, the principal moments of objects can be computed from this normalized quadtree representation. These features make it an information-preserving shape descriptor and suitable for tasks such as object recognition.
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