The invention relates to the technical field of intelligent
agriculture, and discloses a facility vegetable field
prediction system and method based on multi-
modal vision, and the
system comprises a terminal control and data
collection system which is used for carrying out the image collection of the growth condition of
leafy vegetables in a vegetable field; the
data processing system is used for denoising, correcting and registering the images and aligning the images of different modalities in space; and the
data analysis system reconstructs a 3D model of the
plant by using
point cloud data of a depth camera or
LiDAR, and constructs an integrated
sensing system of a two-dimensional form, a three-dimensional structure, a physiological state and a
moisture condition by fusing RGB, hyperspectrum, depth and thermal imaging multi-mode
image acquisition equipment. According to the system, the technical
bottleneck of one-sided information of a single sensor is effectively overcome, the number of leaf vegetables, the
canopy volume, the
chlorophyll content, the
canopy temperature and key parameters directly related to yield formation can be synchronously obtained, and a
solid data foundation is laid for high-precision yield prediction.