Task-focused modeling in automated agriculture

Mark Richard Vriesenga; K. Peleg; Jack Sklansky

doi:10.1117/12.139068

12 January 1993 Task-focused modeling in automated agriculture

Mark Richard Vriesenga, K. Peleg, Jack Sklansky

Proceedings Volume 1771, Applications of Digital Image Processing XV; (1993) https://doi.org/10.1117/12.139068
Event: San Diego '92, 1992, San Diego, CA, United States

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.

Citation Download Citation

Mark Richard Vriesenga, K. Peleg, and Jack Sklansky "Task-focused modeling in automated agriculture", Proc. SPIE 1771, Applications of Digital Image Processing XV, (12 January 1993); https://doi.org/10.1117/12.139068

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