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Parallel Region Property Computation by Active Quadtree Networks
June 1981 (vol. 3 no. 6)
pp. 626-633
Tsvi Dubitzki, Computer Vision Laboratory, Computer Science Center, University of Maryland, College Park, MD 20742; ELEX Control Systems, Israel.
Angela Y. Wu, Computer Vision Laboratory, Computer Science Center, University of Maryland, College Park, MD 20742; Department of Mathematics, Statistics, and Computer Science, American Universit
Azriel Rosenfeld, FELLOW, IEEE, Computer Vision Laboratory, Computer Science Center, University of Maryland, College Park, MD 20742.
Given a binary image stored in a cellular array, a local reconfiguration process can be used to reconnect some of the cells into a quadtree network representing the image. This quadtree can also be ``roped,'' i.e., nodes representing adjacent image blocks of the same size can be joined. Using the roped quadtree network as a parallel (cellular) computer, image properties such as perimeter and genus, as well as the quadtree distance transform, can be computed in O(tree height) = O(log image diameter) time. The area and centroid of the image can be computed in O(height) time without the need for roping.
Citation:
Tsvi Dubitzki, Angela Y. Wu, Azriel Rosenfeld, "Parallel Region Property Computation by Active Quadtree Networks," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 3, no. 6, pp. 626-633, June 1981, doi:10.1109/TPAMI.1981.4767163
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