Geometric modeling using octree encoding

A family of algorithms and extensions provides a computationally efficient means of displaying shaded, semitransparent 3-D objects.

Display Techniques for Octree-Encoded Objects

The space efficiency of quadtrees

A multistage classifier with general tree structure has been developed to recognize a large number of Chinese characters A simple and efficient method of classifying the characters was achieved by choosing the best feature at each stage of the tree The features used are Walsh coefficients obtained from two profiles of a character projected onto the X-Y orthogonal axes Some algorithms for aligning the characters were compared and one of them was adopted in this recognition scheme A high recognition rate of about 995 percent was obtained in an experiment with more than 3000 different Chinese characters

Application of a Multilayer Decision Tree in Computer Recognition of Chinese Characters

Two-dimensional run-encoding (2DRE) is a new file structuring method for quadtree representation which does not use explicit pointers. The structure is based on the assignment of linear keys to each cell in an image, and uses these keys to encode maximal leaves. It is shown that storage requirements for such a structure can be reduced by run-encoding the leaves on the value information. Values are extended from the binary encoding of most previous quadtree research, to multivalue (multicolored) encoding, offering greater flexibility, particularly in the field of geographic information processing. Methods for encoding, decoding, search, and overlay (union, intersection) are presented, and shown to be similar to those acting on other quadtree structures in terms of time complexity. The space-efficiency of 2DRE files is similar or superior to other forms of quadtrees.

Two-dimensional run-encoding for quadtree representation

: An algorithm is presented for obtaining a raster representation for an image given its quadtree For each raster row the algorithm visits the appropriate nodes in the quadtree and, for each such node, outputs a run of length equal to the width of the corresponding block Each block's node is visited as many times as it is high Analysis of the algorithm reveals that its execution time is proportional to the sum of the heights of the blocks comprising the image The total number of terminal and non-terminal nodes visited by the algorithm is also computed and shown to be a function of the number of maximal black and white blocks in the image This means that the algorithm's execution time is directly proportional to the complexity of the image

http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA084288&Location=U2&doc=GetTRDoc.pdf

Region Representation: Quadtree-to-Raster Conversion

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Region Representation: Quadtree-to-Raster Conversion