In the traditional image matching algorithm based on feature poi nts cause a high matching error rate,and the low measurement accuracy of binocul ar vision syst em,so binocular vision ranging method based on improved ORB algorithm was propos ed.First,guided filtering was used to preprocess the image,then the feature poin t detected b y FAST was used as the center to get the area surrounding the feature point,the area was divided,the centroid coordinates of the left and right areas was obtained respectively,the main direc tion was dete rmined according to the two centroid coordinates;then the Sobel operator was use d to calculat e the horizontal and vertical gradients of the pixels,the larger value of the ho rizontal and ve rtical gradient between each pixel pair was compared,finally,the comparison resu lts were st ringed into a binary string form to form descriptor and the Hamming distance was used to match;F inally,in the measurement process,the two-dimensional quadratic function fittin g method w as used to get the sub-pixel coordinates of the feature points,and the three-dimensional coor dinates of the feature points were obtained through the principle of triangulation,so the size of the measured object was obtained.Experimental results show that the matching accuracy of the improved algorithm in this paper is 35.25% higher than that of the traditional O RB,and the minimum relative error of measuring reaches 0.4284%, which meets the measurement requirements.