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Proceedings Paper

Task-focused modeling in automated agriculture
Author(s): Mark Richard Vriesenga; K. Peleg; Jack Sklansky
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Paper Abstract

Machine vision systems analyze image data to carry out automation tasks. Our interest is in machine vision systems that rely on models to achieve their designed task. When the model is interrogated from an a priori menu of questions, the model need not be complete. Instead, the machine vision system can use a partial model that contains a large amount of information in regions of interest and less information elsewhere. We propose an adaptive modeling scheme for machine vision, called task-focused modeling, which constructs a model having just sufficient detail to carry out the specified task. The model is detailed in regions of interest to the task and is less detailed elsewhere. This focusing effect saves time and reduces the computational effort expended by the machine vision system. We illustrate task-focused modeling by an example involving real-time micropropagation of plants in automated agriculture.

Paper Details

Date Published: 12 January 1993
PDF: 7 pages
Proc. SPIE 1771, Applications of Digital Image Processing XV, (12 January 1993); doi: 10.1117/12.139068
Show Author Affiliations
Mark Richard Vriesenga, Univ. of California/Irvine (United States)
K. Peleg, Technion--Israel Institute of Technology (United States)
Jack Sklansky, Univ. of California/Irvine (United States)

Published in SPIE Proceedings Vol. 1771:
Applications of Digital Image Processing XV
Andrew G. Tescher, Editor(s)

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