Translator Disclaimer
14 January 1999 Electro-optical-based machine vision for weed identification
Author Affiliations +
Proceedings Volume 3543, Precision Agriculture and Biological Quality; (1999)
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States
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.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Liviu Singher "Electro-optical-based machine vision for weed identification", Proc. SPIE 3543, Precision Agriculture and Biological Quality, (14 January 1999);


Nonlinear Fourier correlation
Proceedings of SPIE (April 13 2009)
Nonlinear filtering of images in optical-digital processors
Proceedings of SPIE (January 19 1995)
Tanks in trees a case study of ternary phase...
Proceedings of SPIE (September 29 1994)

Back to Top