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Processor-time optimal parallel algorithms for digitized images on mesh-connected processor arrays

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Abstract

We present processor-time optimal parallel algorithms for several problems onn ×n digitized image arrays, on a mesh-connected array havingp processors and a memory of sizeO(n 2) words. The number of processorsp can vary over the range [1,n 3/2] while providing optimal speedup for these problems. The class of image problems considered here includes labeling the connected components of an image; computing the convex hull, the diameter, and a smallest enclosing box of each component; and computing all closest neighbors. Such problems arise in medium-level vision and require global operations on image pixels. To achieve optimal performance, several efficient data-movement and reduction techniques are developed for the proposed organization.

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Authors and Affiliations

  1. EEB-244, Department of Electrical Engineering Systems, University of Southern California, 90089-2562, Los Angeles, CA, USA

    Hussein M. Alnuweiri & V. K. Prasanna Kumar

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  1. Hussein M. Alnuweiri
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  2. V. K. Prasanna Kumar
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Communicated by Frank Dehne.

This research was supported in part by the National Science Foundation under Grant IRI-8710836 and in part by DARPA under Contract F33615-87-C-1436 monitored by the Wright Patterson Airforce Base.

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Alnuweiri, H.M., Prasanna Kumar, V.K. Processor-time optimal parallel algorithms for digitized images on mesh-connected processor arrays. Algorithmica 6, 698–733 (1991). https://doi.org/10.1007/BF01759068

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  • DOI: https://doi.org/10.1007/BF01759068

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