Electro-optical-based machine vision for weed identification

Liviu Singher

doi:10.1117/12.336895

14 January 1999 Electro-optical-based machine vision for weed identification

Liviu Singher

Proceedings Volume 3543, Precision Agriculture and Biological Quality; (1999) https://doi.org/10.1117/12.336895
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States

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.

Citation Download Citation

Liviu Singher "Electro-optical-based machine vision for weed identification", Proc. SPIE 3543, Precision Agriculture and Biological Quality, (14 January 1999); https://doi.org/10.1117/12.336895

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KEYWORDS

Genetic algorithms

Nonlinear filtering

Optical filters

Image processing

Machine vision

Image filtering

Pattern recognition

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