Development of a multispectral imagery device devoted to weed detection

Multispectral imagery is a large domain with a number of practical applications: thermography and quality control in industry, food science, and agronomy. The main interest is to obtain spectral information of the objects for which a reflectance signal can be associated to physical, chemical, and/or biological properties. Agronomic applications of multispectral imagery generally involve the acquisition of several images in visible and near infrared wavelengths. We first present a different kind of multispectral devices used for agronomic applications and then introduce an original multispectral acquisition system based on a single CCD. First results in laboratory are detailed, presenting a detection method using a neural network and in-field acquisitions and their results are shown. To improve the quality of weed detection, the spatial distribution of crops is used by a second method. Finally, the first works on merging are outlined.