Abstract
This paper summarizes the authors' research in imaging- and optical weed sensors based on studies of plant spectral and morphological characteristics. Location, color, texture, and shape features of weeds and crops were identified as the major criteria for sensor structure and algorithm design. Imaging-based weed sensors were compared with optical weed sensors. Factors affecting detection accuracy were studied through experiments. Laboratory experiments were also conducted to test the accuracy of statistical and neural-network classification models. Extensive field experiments were conducted to test the effectiveness of the weed sensors.
