1. A computer-implemented method for processing a block to be processed of a urine sediment image by a processor executing executable instructions stored in a non-transitory memory, the method comprising: dividing the block to be processed of the urine sediment image into a plurality of grids according to a predetermined division rule; calculating an n-dimensional local feature vector of each grid of the plurality of grids, where n is a positive integer, wherein calculating the n-dimensional local feature vector of each grid of the plurality of grids comprises: calculating a gradient value and a gradient direction of each pixel in the grid, wherein the gradient direction is approximated to one of n predetermined standard directions; and calculating a total gradient value of a pixel with a pixel gradient direction being approximated to a specific standard direction in the n standard directions in the grid as one dimension of an n-dimensional local feature vector of the grid, with a total gradient value of a respective pixel in the n standard directions corresponding to n dimensions of the n-dimensional local feature vector; in the block of the urine sediment image to be processed, according to a predetermined merging rule, merging at least two adjacent grids of the plurality of grids into an intermediate block; according to the n-dimensional local feature vectors of the grids contained in the intermediate block, calculating an intermediate block merging feature vector of the intermediate block; according to a predetermined combination rule, combining the intermediate block merging feature vectors obtained for different intermediate blocks of the block to be processed into a general combination feature vector of the block to be processed; and using the general combination feature vector as a feature in a feature set of block processing to process the block of the urine sediment image to be processed.