三角網格資料特徵分離之研究

Research of Feature Segmentation Technique for Triangular Meshes

陳志瑋(Chih-Wei Chen)

指導教授 ： 賴景義

國立中央大學/工學院/機械工程學系/碩士(2007年)

摘要

逆向工程為一種由實體模型的三維量測資料重建CAD模型的技術，點資料處理則是逆向工程裡最重要的一環。因大量的點資料會提高CAD重建的困難度，因此，本研究的主要目的是發展一系列的網格資料特徵分離技術，依照工件的幾何特性將網格資料進行區域分離。對於二次曲面及自由曲面有不同的處理方式，針對簡單的二次曲面如平面、圓柱與圓錐等網格資料，發展一套完整的分離流程，只針對種子點附近的區域進行處理，以減少分離網格資料的時間；針對幾何型態較為複雜的自由曲面，則以多種基礎幾何之運算進行特徵辨識，並將特徵區域進行最佳化處理，再以曲率方向的運用，刪除不為封閉的特徵區域，以達到較佳的分離結果。

關鍵字

特徵分離 ； 逆向工程 ； 主曲率 ； 主軸方向

並列摘要

Reverse engineering is a technique to reconstruct the CAD model from the three-dimensional measurement points of a physical object. The pre-processing of the data points is most important because a large number of data points may lead difficulty to reconstruct the CAD model. The main objective of this research is to develop a series of feature segmentation technique for the triangular meshes in terms of the geometric characteristics of the model. There are different ways to deal with the quadratic surfaces and freeform surfaces. For quadratic surfaces such as plane, cylinder and cone, we develop a procedure for the segmentation of the triangular meshes corresponding to such features, and only operate in the nearby area of the seed point so as to reduce the time required in processing the data. For the freeform surfaces with complicated geometric characteristics, we apply many kinds of operations to recognize and optimize different feature regions from triangular meshes. Then we delete redundant vertices in each feature regions in terms of the curvature information so as to yield clean and un-noised segmentation results.

並列關鍵字

reverse engineering ； principal curvature ； feature segmentation ； principal direction

參考文獻

[1]G. Taubin, “Estimating the Tensor of Curvature of a Surface from a Polyhedral Approximation”, Proceedings of the 5th International Conference on Computer Vision , pp. 902-907, 1995.

[2]P. Krsek, G. Lukacs and R. R. Martin,“Algorithms for Computing Curvatures from Range Data”, Mathematics of Surfaces VIII, pp. 1-16, 1998.

[3]J. A. Thorpe, Elementary Topics in Differential Geometry, Springer-Verlag, 1978.

[4]T. Surazhsky, E. Magid, O. Soldea, G. Elber, E. Rivlin, “A Comparison of Gaussion and Mean Curvatures Estimation Methods on Triangular Meshes”, Proceedings of The IEEE International Conference on Robotics and Automation, 2003.

[5]A. F. Koschan, D. L. Page and M. A. Abidi, “Perception-based 3D Triangle Mesh Segmentation Using Fast Marching Watersheds”, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2, pp. 27-32, 2003.