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Proceedings Paper

Fuzzy logic inference systems for discriminating plants from soil and residue with machine vision
Author(s): Timothy W. Hindman; George E. Meyer
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Paper Abstract

This paper summarizes the theory of fuzzy inference systems and its application to plant and weed detection. Two simple examples are presented, both of which discriminate between plants and soil and residue backgrounds in color images based on derived excess green and excess red color indices. The first example shows that a numerical excess red model can be readily replaced with a fuzzy inference system, based on training of red, green, and blue inputs and excess red. The second example shows an arbitrary system of fuzzy inference with excess red and excess green using human preselection, which also gives satisfactory discrimination results.

Paper Details

Date Published: 29 December 2000
PDF: 11 pages
Proc. SPIE 4203, Biological Quality and Precision Agriculture II, (29 December 2000); doi: 10.1117/12.411745
Show Author Affiliations
Timothy W. Hindman, Univ. of Nebraska/Lincoln (United States)
George E. Meyer, Univ. of Nebraska/Lincoln (United States)

Published in SPIE Proceedings Vol. 4203:
Biological Quality and Precision Agriculture II
James A. DeShazer; George E. Meyer, Editor(s)

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