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Proceedings Paper

A Hybrid SIMD/MIMD Architecture For Image Understanding
Author(s): Kai Hwang; V K. Prasanna Kumar; Dongseung Kim; Hussein M. Alnuweiri
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Paper Abstract

This paper presents an integrated parallel architecture for image analysis and computer vision. The architecture consists of an SIMD array processor with multiple broadcast busses, an MIMD multiprocessor with orthogonal access busses, and a two-dimensional memory array shared by both processor systems. Low-level image processing is performed on the SIMD array, while interme-diate and high-level image analysis is performed on the multiprocessor system. The interaction between the two levels is supported by a common shared memory. To illustrate the power of such a two-level system we show that a wide class of image and vision analysis tasks can be performed efficiently on the architecture. Representative problems include transitive closure, histogramming image component labeling, pyramid computation, Hough transform, pattern clustering, and scene labeling.

Paper Details

Date Published: 17 May 1989
PDF: 12 pages
Proc. SPIE 1058, High Speed Computing II, (17 May 1989); doi: 10.1117/12.951662
Show Author Affiliations
Kai Hwang, University of Southern. California (United States)
V K. Prasanna Kumar, University of Southern. California (United States)
Dongseung Kim, University of Southern. California (United States)
Hussein M. Alnuweiri, University of Southern. California (United States)

Published in SPIE Proceedings Vol. 1058:
High Speed Computing II
Keith Bromley, Editor(s)

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