Weed detection by analysis of multispectral images acquired under uncontrolled illumination conditions

Localized weed control is one of the promising solutions to improve the application of herbicides in crop fields. To target weeds exclusively during the spray, their location in the field must be accurately determined. As weeds have colorimetric properties similar to crops, their detection may be difficult especially under varying illumination conditions. Among available technologies, multispectral cameras provide radiance images with a high spectral resolution allowing for the analysis of vegetation signatures beyond the visible and near infrared domains. In this study, we address the problem of outdoor weed detection and identification using multispectral and RGB-NIR imaging.