Prediction of Corn Growth Based on Digital Image Processing Technology

Corn growth refers to status and trends of corn growth.In the growth period，the key of corn production regulation is to real time know growth.Growth of corn can be measured by leaf area，tip distance of leaf and leaf base angle.Jilin province is the main corn planting area in China and planting scale is mostly small plots.If traditional manual method was used to measure growth of corn，it would take a lot of manpower and material resources.While remote sensing technology was suitable for planting in a large area.Therefore，manual measurement and remote sensing technology had obvious limitations.Digital image processing technology was used and multi scale images of corn at different growth stages were obtained by fixed image acquisition equipment.First，grayscale and enhancement techniques were used to preprocess images.Then，an iterative threshold segmentation algorithm was used to extract corn region in the image.Parameters of corn plant height，tip distance of leaf，leaf base angle and canopy area were obtained through image thinning technology which combined with reference calibration method.Finally，corn growth model was established by regression analysis on acquired characteristic parameters.Test results showed that the method was effective and feasible.And it could be served as a necessary and useful supplement to manual measurement and remote sensing technology.