JOURNAL ARTICLE

<title>Machine vision testbed</title>

Robert LyonsDavid GibbonJakub SegenBehzad ShahraraySriram Ganapathy

Year: 1993 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 2064 Pages: 251-263   Publisher: SPIE

Abstract

The Machine Vision Testbed (MVT) is an integrated hardware and software environment for prototyping machine vision algorithms. The system incorporates special purpose image processing hardware (Datacube MaxVideo20TM,) multiple high performance general purpose computers (SKYboltTM) and a Sun SPARCengine 1ETM. A software environment provides the Sun processor with the capability to thread and control tasks amongst various processing elements. To support video processing requirements, special purpose hardware has been designed which provides an image broadcast bus from the Maxvideo20 into multiple SKYbolt processors. The underlying programming model for the system is to use the special purpose image processing hardware to perform computationally intensive image processing tasks and to have the local (or neighborhood) type operations run on the general purpose processors. This partitioning provides a path to migrate large portions of an application, which would typically run on special purpose hardware, onto fast general purpose processors for the purposes of software reuse and portability. This paper is intended to discuss the motivation for choosing such a hybrid architecture and to discuss the details of how such a heterogeneous collection of components was integrated into a system capable of processing video data.

Keywords:
Computer science Testbed Software portability Image processing Software Embedded system Computer hardware Thread (computing) Hardware architecture Field-programmable gate array Operating system Computer architecture Artificial intelligence Image (mathematics)

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Topics

CCD and CMOS Imaging Sensors
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced Neural Network Applications
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Infrared Target Detection Methodologies
Physical Sciences →  Engineering →  Aerospace Engineering

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