title: Validation of a crop field modeling to simulate agronomic images.
abstract: In precision agriculture, crop/weed discrimination is often based on image analysis but though several algorithms using spatial information have been proposed, not any has been tested on relevant databases. A simple model that simulates virtual fields is developed to evaluate these algorithms. Virtual fields are made of crops, arranged according to agricultural practices and represented by simple patterns, and weeds that are spatially distributed using a statistical approach. It ensures a user-defined Weed Infestation Rate (WIR). Then, experimental devices using cameras are simulated with a pinhole model. Its ability to characterize the spatial reality is demonstrated through different pairs (real, virtual) of pictures. Two spatial descriptors (nearest neighbor method and Besag's function) have been set up and tested to validate the spatial realism of the crop field model, comparing a real image to the homologous virtual one.
authors.affiliation: AgroSup Dijon, Unité Propre GAP: Génie des Agro-équipements et des Procédés, 26 Bld Dr Petitjean, BP 87999, 21079 Dijon Cedex, France.
authors.forename: Gawain
authors.initials: G
authors.lastname: Jones
authors.forename: Christelle
authors.initials: C
authors.lastname: Gée
authors.forename: Sylvain
authors.initials: S
authors.lastname: Villette
authors.forename: Frédéric
authors.initials: F
authors.lastname: Truchetet
mesh_terms: D003198:Computer Simulation; D018556:Crops, Agricultural / Q000033:anatomy & histology*; D004784:Environmental Monitoring / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008953:Models, Anatomic; D010781:Photography / Q000379:methods*; D010944:Plants / Q000033:anatomy & histology*