Image segmentation for measuring growth coefficients of wheat used in precision agriculture

Water deficit affects several physiological variables of the plant and is synonymous with a decrease in yield and quality for field crops such as wheat. Irrigation is therefore a recommended solution. Agronomic image processing has enabled the development of several tools to deal with the phenomenon, by combining sensors and models such as the percentage of soil cover PGC and crop coefficient Kc. The aim of our work is the development of an indicator of the condition of the crop plants, accessible by video surveillance using image segmentation based on the multiphase level set model, allowing the early detection and prevention of water stress. Repeated images were taken on control plants at several stages of crop development.