Adaptive Slicing Algorithm Based on Projected Contour Area of Point Cloud

Aiming at the problems of sparse contour points extracted by existing slicing methods, long operation time of layer-by-layer contour point interpolation method, and significant shape errors caused by uniform slicing, an adaptive slicing algorithm based on point cloud projection contour area was proposed. Based on the moving least squares method, the algorithm increases the sampling of the whole point cloud model to increase the high point cloud density and can adjust the slice thickness according to the ratio of the inner and outer contour area of the projected point cloud. The results show that the algorithm can effectively avoid the absence of contour points, and the average distance between slice contour points is only 0.04 mm. Compared with other slice methods, the obtained slice results have clearer contour details, and the structural similarity is increased by more than $5 \%$, which can meet the needs of skin printing and lay a foundation for the subsequent skin printing repair test.