Region-based layered infill area generation of STL models for additive manufacturing

Purpose In the implementation of large-size additive manufacturing (AM), the large printing area can be established by using the tiled and fixed multiple printing heads or the single dynamic printing head moving in the x–y plane, which requires a layer decomposition after the mesh slicing to generate segmented infill areas. The data processing flow of these schemes is redundant and inefficient to some extent, especially for the processing of complex stereolithograph (STL) models. It is of great importance in improving the overall efficiency of large-size AM technics software by simplifying the redundant steps. This paper aims to address these issues. Design/methodology/approach In this paper, a method of directly generating segmented layered infill areas is proposed for AM. Initially, a vertices–mesh hybrid representation of STL models is constructed based on a divide-and-conquer strategy. Then, a trimming–mapping procedure is performed on sliced contours acquired from partial surfaces. Finally, to link trimmed open contours and inside-signal square corners as segmented infill areas, a region-based open contour closing algorithm is carried out in virtue of the developed data structures. Findings In virtue of the proposed approach, the segmented layered infill areas can be directly generated from STL models. Experimental results indicate that the approach brings us the good property of efficiency, especially for complex STL models. Practical implications The proposed approach can generate segmented layered infill areas efficiently in some cases. Originality/value The region-based layered infill area generation approach discussed here will be a supplement to current data process technologies in large-size AM, which is very suitable for parallel processing and enables us to improve the efficiency of large-size AM technics software.

A New Algorithm of Image Registration Based on Contour Feature

Image registration is an important task in image processing. In this paper, a new and fast contour-based image registration algorithm is proposed. In this algorithm, we fetch contour points and calculate the normal angles firstly, then figure out the histogram of the contour-feature points. By computing circular correlation of the histogram, the rotation angle can be gained. As the rotation angle is obtained, it vastly simplifies the complexity of estimating other registration parameters and reduces the calculated amount, thus achieving a fast image registration algorithm. This algorithm has the invariance of rotation, translation and scale, and it has high robustness for either open contour or closed contour.