3D image monitoring and modeling for corn plants growth in field condition

Some growth parameters of corn plants were measured in field based on binocular stereovision technology, and a 3D structure model of corn plants was established. The average height of corn plants measured in previous period was established as the base plane of measure area, which binarized by Ostu method. The measure region was divided into grids. The plant area and the average color were measured by matching these grids on left and right visions. The point cloud consisted of grid’s core was established by the 3D reconstructing of these grids. The average height of corn plant was calculated by using the point cloud, and validated by measuring the labeled pole. The 3D structure model of corn plant was established with above data by OpenGL. This study established a base work to real time measure the plant value without scathe, and to model the 3D plant more accurately.