Automatic identification of weed species using digital processing
1994
Soekefeld, M. (Bonn Univ. (Germany). Lehrstuhl fuer Allgemeinen Pflanzenbau) | Gerhards, R. | Kuehbauch, W.
Plant species discrimination in mixed plant communities has recently become possible using transforms and shape parameters to classify images. In the present study image analysis techniques were used to identify 22 weed species commonly found in sugarbeet fields. Images of several growth stages of these weeds were photographed using a CCD-Videocamera, binarified, the shape extracted and then Fourier descriptors and shape parameter were calculated for each weed.Classified digital images of each species were stored on the computer. A separate set of photographic images of these 22 weeds were used to test the ability of the classified images for plant identification. The average rate of correct identification was 69.5% for weeds with only cotyledons and 75.4% for weeds with one or two pairs of leaves
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