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Proceedings Paper

Overview of AIM: supporting computer vision on heterogeneous high-performance computing systems
Author(s): Monica Sweat; Joseph N. Wilson
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Paper Abstract

The AIM (Adaptive Image Manager) is a client/server based system providing a computer vision and image processing specific protocol that interfaces to potentially numerous varying computing platforms providing image processing and computer vision support. It provides a unified programming interface for the user despite the potential heterogeneity of the underlying hardware supporting the image processing. Computational platforms currently being studied include the Lockheed Martin PAL system, floating point gate arrays, and symmetric multiprocessors. The Open Distributed Processing Reference Model (ODP-RM) is an ISO standards effort (ISO/IEC 10746-1/2/3/4) to address the specification and implementation f distributed processing systems, providing an architecture for integrating distribution support, interworking, and portability. The ODP Reference Model is exploited in the design to support transparent distribution of image processing and computer vision processes to available computational devices. The AIM System's ODP Model is specified using Object-Z, a formal descriptive notation that is commonly employed for ODP specification. Use of Object-Z notation supports formal analysis of the system's properties, helping us verify that its design satisfies its goals. This paper presents an example image processing algorithm (Simple Image Statistic Thresholding) as a framework for understanding both the method of distribution and the benefits obtained from the use of our model description.

Paper Details

Date Published: 21 September 1998
PDF: 12 pages
Proc. SPIE 3452, Parallel and Distributed Methods for Image Processing II, (21 September 1998); doi: 10.1117/12.323476
Show Author Affiliations
Monica Sweat, Univ. of Florida (United States)
Joseph N. Wilson, Univ. of Florida (United States)

Published in SPIE Proceedings Vol. 3452:
Parallel and Distributed Methods for Image Processing II
Hongchi Shi; Patrick C. Coffield, Editor(s)

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