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Analysis of parallel algorithms using pipeline architectures in computer vision applications

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Abstract

Recently a number of machine vision systems have been successfully implemented using pipeline architectures and various new algorithms have been proposed. In this paper we propose a method of analysis of both time complexity and space complexity for algorithms using conventional general purpose pipeline architectures. We illustrate our method by applying it to an algorithm schema for local window operations satisfying a property we define as decomposability. It is shown that the proposed algorithm schema and its analysis generalize previous published results. We further analyse algorithms implementing operators that are not decomposable. In particular the complexities of several median-type operations are compared and the implication on algorithm choice is discussed. We conclude with discussions on space-time trade-offs and implementation issues.

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Authors and Affiliations

  1. Department of Computer Science, The Hong Kong University of Science and Technology, Clear Water Bay Rd., Tai Po Tsai, Kowloon, Hong Kong

    Amelia Fong Lochovsky

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  1. Amelia Fong Lochovsky
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Additional information

This research was partially supported by a grant from the Natural Science and Engineering Research Council of Canada. Part of this work was done while the author was at the University of Guelph, Guelph, Ontario, Canada.

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Fong Lochovsky, A. Analysis of parallel algorithms using pipeline architectures in computer vision applications. Ann Math Artif Intell 4, 177–209 (1991). https://doi.org/10.1007/BF01531178

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