  Reconstructing and processing the 3D objects are popular activities in the
research field of computer graphics, image processing and computer vision. The
3D objects are processed based on the methods like geometric modeling, a branch
of applied mathematics and computational geometry, or the machine learning
algorithms based on image processing. The computation of geometrical objects
includes processing the curves and surfaces, subdivision, simplification,
meshing, holes filling, reconstructing, and refining the 3D surface objects on
both point cloud data and triangular mesh. While the machine learning methods
are developed using deep learning models. With the support of 3D laser scan
devices and Lidar techniques, the obtained dataset is close to original shape
of the real objects. Besides, the photography and its application based on the
modern techniques in recent years help us collect data and process the 3D
models more precise. This article proposes an improved method for filling holes
on the 3D object surface based on an automatic segmentation. Instead of filling
the hole directly as the existing methods, we now subdivide the hole before
filling it. The hole is first determined and segmented automatically based on
computation of its local curvature. It is then filled on each part of the hole
to match its local curvature shape. The method can work on both 3D point cloud
surfaces and triangular mesh surface. Comparing to the state of the art
methods, our proposed method obtained higher accuracy of the reconstructed 3D
objects.
