The invention discloses a
scindapsus aureus leaf shape parameter
estimation method based on MRE-Point Net and an auto-
encoder model, and the method comprises the steps: carrying out the photographingof
scindapsus aureus from a single angle through a Kinect V2 camera, obtaining
point cloud data, carrying out the preprocessing of the data through straight-through filtering, segmentation and
point cloud simplification algorithms, building a
scindapsus aureus leaf geometric model through a
parameter equation, and calculating the blade length, the blade width and the blade area of the geometric model; and inputting the discrete
point cloud data of the geometric model into a multi-resolution point cloud
deep learning network to obtain a pre-training model, and taking the discrete point
cloud data of the geometric model as input to obtain a pre-training model of an auto-
encoder through encoding and decoding operation, performing secondary
processing noise reduction is performed on input point
cloud data through a pre-training model of an auto-
encoder, and then parameter fine adjustment is performed on the pre-training model by using the measured scindapsus aureus leaf shape parameter
label so that shape parameter
estimation of the input scindapsus aureus leaf point
cloud data can be completed.