Electronic recognition of plant species for machine vision sprayer control systems

Author

Runtz, K.J.

Author_Institution

Fac. of Eng., Regina Univ., Sask., Canada

fYear

1991

fDate

29-30 May 1991

Firstpage

84

Lastpage

88

Abstract

It is noted that machine vision systems have the potential as sprayer controllers to reduce farm chemical use and to increase the effectiveness of crop spraying operations. The author examines the issues in developing real-time plant recognition algorithms and associated electronic hardware. A very efficient algorithm for distinguishing between broadleaf and grassy plant species is proposed. Preliminary tests on video images of several types of field crops are reported. These tests show the potential for this and related image processing algorithms as plant classifiers in real-time systems

Keywords

agriculture; computer vision; computerised control; computerised pattern recognition; computerised picture processing; real-time systems; broadleaf series; crop spraying; electronic hardware; field crops; grassy plant species; image processing algorithms; machine vision sprayer control systems; real-time plant recognition algorithms; video images; Automatic control; Chemicals; Control systems; Costs; Crops; Machine vision; Production; Soil; Sorting; Spraying;

fLanguage

English

Publisher

ieee

Conference_Titel

WESCANEX '91 'IEEE Western Canada Conference on Computer, Power and Communications Systems in a Rural Environment'

Conference_Location

Regina, Sask.

Print_ISBN

0-87942-594-6

Type

conf

DOI

10.1109/WESCAN.1991.160525

Filename

160525