Intelligent image recognition of particle size and gradation of earth-rock

The gradation of soil and stone materials directly affects the quality and anti-seepage of earth-rock dams. In order to solve the low efficiency and randomness of the traditional manual screening and the visual removal of oversized particles, the image recognition technology based on the MaskRCNN algorithm is used to start with the image recognition of standard spheres, and the relationship between the number of recognized spheres and the real number under different groups of particle sizes is studied. The ellipsoid calculation method that extends particle plane recognition to space volume is proposed, and the transformation method between the image recognition and the gradation based on the exponential function is established. By applying this method to the identification of particle size and the gradation of crushed stone and gravel, the correlation coefficient increases by more than 10%, and the accuracy of C_u and C_c reflected by the gradation curve is up to 35.26%. This stud may provide a new method for the image recognition of soil and stone gradation.