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Issue No.01 - January (1993 vol.15)
pp: 69-81
ABSTRACT
<p>Describes two parallel algorithms for ranking the pixels on a curve in O (log N) time using either an EREW or CREW PRAM model. The algorithms accomplish this with N processors for a square root N* square root N image. After applying such an algorithm to an image, it is possible to move the pixels from a curve into processors having consecutive addresses. This is important because one can subsequently apply many algorithms to the curve (such as piecewise linear approximation algorithms or point in polygon tests) using segmented scan operations (i.e. parallel prefix operations). Scan operations can be executed in logarithmic time on many interconnection networks, such as hypercube, tree, butterfly, and shuffle exchange machines as well as on the EREW PRAM. The algorithms were implemented on the hypercube structured Connection Machine, and various performance tests were conducted.</p>
INDEX TERMS
EREW model; computer vision; parallel processing; image contours; parallel algorithms; CREW PRAM model; segmented scan operations; hypercube; Connection Machine; computational complexity; computer vision; hypercube networks; image processing; parallel algorithms; parallel processing
CITATION
L.T. Chen, L.S. Davis, C.P. Kruskal, "Efficient Parallel Processing of Image Contours", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.15, no. 1, pp. 69-81, January 1993, doi:10.1109/34.184775
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