Aiming at the problem that the existing parameter measurement methods are difficult to effectively measure the parameters of cross-linked polyethylene cable joint, a cable joint parameter measurement method based on three-dimensional point cloud segmentation is proposed. Firstly, radius filtering and random sample consensus (RANSAC) algorithm are used to remove the noise points and preprocess the coordinate alignment of the cable joint point cloud obtained by the composite 3D scanner. Then, the RANSAC algorithm is used to fit the cable joint point cloud to a circle, and the rough segmentation is realized according to the mutation characteristic of the ratio of radius variance of adjacent fitting circles at the regional junction, so as to obtain multiple local point clouds containing regional junction points. Next, the normals of the local point clouds were estimated using principal component analysis, and the regional junction values were derived from the jump characteristics of the axial angles of the point clouds at the regional junction points and the adaptive threshold algorithm. Finally, a statistical analysis of the junction values of the same area obtained from multiple strip point clouds was carried out to achieve a fine segmentation of the cable joint point cloud and complete the parameter measurement. The results of the measurement experiments on several cable joints show that the absolute error of the proposed method is less than 1. 0 mm and the relative error is less than 4%, which demonstrates the validity and accuracy of the method for measuring the parameters of cross-linked polyethylene cable joint.