An Automatic Measurement Method and System for Material Quantity in Silos Based on Machine Vision

Abstract

This invention belongs to the field of image processing technology, specifically relating to an automatic measurement method and system for material quantity in a silo based on machine vision. The method includes: acquiring depth and infrared intensity images of the silo; preprocessing these images to generate a valid binary mask; determining a geometric confidence factor based on the deviation between the depth gradient and the natural angle of repose of the material being measured, as well as local curvature; and determining an environmental confidence factor by combining infrared intensity and measurement distance; repairing invalid pixels using anisotropic diffusion; predicting depth values ​​based on first-order Taylor expansion and multi-dimensional confidence weighting; converting the repaired depth image into physical height and projected area; and obtaining the total volume of material in the silo through infinitesimal element accumulation. This invention solves the problem of data loss in complex environments and improves measurement accuracy.

Images