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Proceedings Paper

Electro-optical-based machine vision for weed identification
Author(s): Liviu Singher
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Paper Abstract

This work evaluates real-time techniques for a novel concept of identifying weeds, location and extraction of outline features. THE proposed techniques are conducted by electro- optical methods and perform with the speed of light. The optical system is compact, easy to align and uses a small number of inexpensive components. Generating the 'right' filter for a pattern recognition problem is presented as an optimization process for which the filter performance is the function to be maximized. The genetic algorithm is introduce as a search procedure that uses a biologically motivated random choice as a tool to guide a highly exploitative search through the filter space for nonlinear correlation. The features of the genetic algorithm are ideal for a highly efficient and fast learning process. Computer simulations demonstrate very efficient pattern recognition and excellent discrimination.

Paper Details

Date Published: 14 January 1999
PDF: 8 pages
Proc. SPIE 3543, Precision Agriculture and Biological Quality, (14 January 1999); doi: 10.1117/12.336895
Show Author Affiliations
Liviu Singher, Technion-Israel Institute of Technology (Israel)

Published in SPIE Proceedings Vol. 3543:
Precision Agriculture and Biological Quality
George E. Meyer; James A. DeShazer, Editor(s)

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