DocumentCode
116252
Title
Study of variable spray control system based on machine vision
Author
Rui Zhang ; Lepeng Song
Author_Institution
Coll. of Electr. & Inf. Eng., Chongqing Univ. of Sci. & Technol., Chongqing, China
fYear
2014
fDate
18-20 Aug. 2014
Firstpage
455
Lastpage
458
Abstract
This system captures and analyses the growth of crops based on machine vision technology, controlled by the PLC variables and achieve the objective of saving fertilizer, improving economic efficiency and protecting the environment. It uses shape or texture of the crops and background information contained in the image to classify, builds database algorithms, processes the collecting real-time signal by the internal computer and provides a spray flow rate required by the target area of operation, thus achieves variable spray to the target automatically. As a result, the real-time database of the precision agriculture variable spray is created; the system then receives the target spray flow signals on the intelligent platform and variable sprays with an intelligent spray operation platform speed.
Keywords
computer vision; crops; environmental factors; fertilisers; image classification; image texture; precision engineering; programmable controllers; shape recognition; sprays; PLC variables; crop growth analysis; crop shape; crop texture; economic efficiency; environment protection; fertilizer saving; image classification; intelligent spray operation platform speed; machine vision; machine vision technology; precision agriculture variable spray; real-time database; real-time signal; spray flow rate; variable spray control system; Agriculture; Computers; Control systems; Image segmentation; Machine vision; Real-time systems; Valves; machine vision; precision agriculture; variable spray;
fLanguage
English
Publisher
ieee
Conference_Titel
Cognitive Informatics & Cognitive Computing (ICCI*CC), 2014 IEEE 13th International Conference on
Conference_Location
London
Print_ISBN
978-1-4799-6080-4
Type
conf
DOI
10.1109/ICCI-CC.2014.6921498
Filename
6921498
Link To Document