Navigation line extraction based on root and stalk composite locating points

Jinliang Gong, Xiangxiang Wang, Yanfei Zhang*, Yubin Lan, Kazi Mostafa

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

The presence of weeds undermines the accurate algorithmic detection of navigation lines in cornfields, which plays a pivotal navigational role in the operation of intelligent agricultural machinery for tasks such as weeding and spraying. A method was proposed for extracting navigation lines by using the composite locations of the root and stalk of corn in the 6th- to 14th-leaf stages growing in a complex environment. The positional and area features were first used to eliminate the interference regions and obtain the root locations. The white pixel percentage index was used to filter the line segments obtained through the Hough transform and thereby determine the stalk locations. Experiments showed that the navigation lines were detected at an accuracy of 93.8%, an improvement of 10.2% over that achieved using conventional methods.

Original languageEnglish
Article number107115
JournalComputers and Electrical Engineering
Volume92
DOIs
Publication statusPublished - Jun 2021
Externally publishedYes

Keywords

  • Composite locating point
  • Machine vision
  • Navigation line
  • Robust regression

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