Shape features for identifying young weeds using image analysis

D. M. Woebbecke, G. E. Meyer, K. Von Bargen, D. A. Mortensen

Research output: Contribution to journalArticlepeer-review

209 Scopus citations


Shape feature analyses were performed on binary images originally obtained from color images of 10 common weeds, along with corn and soybeans, found in the Midwest. Features studied were roundness, aspect, perimeter/thickness, elongatedness, and seven invariant central moments (ICM), for each plant type and age up to 45 days after emergence. Shape features were generally independent of plant size, image rotation, and plant location within most images. The ability to discriminate between monocots and dicots was most evident between 14 and 23 days using these features. Shape features that best distinguished these plants were aspect and first invariant central moment (ICM1), which classified 60 to 90% of the dicots from the monocots. Using Analysis of Variance and Tukey's multiple comparison tests, shape features did not change significantly for most species over the study period. This information could be very useful in the future design of advanced spot spraying applications.

Original languageEnglish (US)
Pages (from-to)271-281
Number of pages11
JournalTransactions of the American Society of Agricultural Engineers
Issue number1
StatePublished - Jan 1995

All Science Journal Classification (ASJC) codes

  • Agricultural and Biological Sciences (miscellaneous)


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