Abstract
As a simplified representation of a geometric model, the medial axis (MA) has been used in a wide range of engineering applications. While obtaining the true MA of a complicated CAD model is known to be a difficult task, current research is predominantly focused on computing its approximate MA instead. To improve its quality, this work develops a novel and efficient method for obtaining a high-quality MA composed of MA faces for a CAD model. Specifically, an MA point is computed using a dual-normal-tracing algorithm for each sample point. This algorithm can be implemented through GPU-enabled parallel computing and be executed in an iterative manner until MA points have been found for all sample points. After the iteration is completed, the MA points generated are then converted into the resultant MA by evaluating the topological connectivities of their corresponding sample points. Finally, the resultant MA is converted into MA faces using the information of boundary CAD faces. The proposed method is evaluated by analyzing its complexity and robustness, discussing its applicability and testing its performance in a couple of computational experiments. As shown in the evaluation, this method is easy to implement through exploiting parallel computing and can support effective and high-quality MA generation for a CAD model.
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References
Blum H (1976) A transformation for extracting new descriptors of shape. In: Wathen-Dunn W (ed) Models for the perception of speech and visual form. MIT Press, Cambridge, pp 362–380
Zhang XL, Xia Y, Wang JY et al (2015) Medial axis tree—an internal supporting structure for 3D printing. Comput Aided Geometr Des 35–36:149–162
Cameron S (1990) Collision detection by 4-dimensional intersection testing. IEEE Trans Robot Autom 6(3):291–302
Attali D. (1998) r-Regular shape reconstruction from unorganized points. Comput Geom: Theory Appl 10(4):239–247
Zhu HS, Liu YS, Bai J et al (2015) Constructive generation of the medial axis for solid models. Comput Aided Des 62:98–111
Zhu HS, Liu YS, Zhao JJ et al (2015) Calculating the medial axis of a CAD model by multi-CPU based parallel computation. Adv Eng Softw 85:96–107
Zhu HS, Liu YS, Zhao JJ (2016) Generation of hierarchical multi-resolution medial axis for CAD models. Adv Eng Softw 94:20–31
Foskey M, Lin MC, Manocha D (2003) Efficient computation of a simplified medial axis. In: Proceedings of the eighth ACM symposium on solid modeling and applications, pp 96–107
Ma J, Bae SW, Cho S (2012) 3D medial axis point approximation using nearest neighbors and the normal field. Vis Comput 28(1):7–19
Ramanathan M, Gurumoorthy B (2010) Interior medial axis computation of 3D objects bound by free-form surfaces. Comput Aided Des 42(12):1217–1231
Attali D, Boissonnat JD, Edelsbrunner H (2009) Stability and computation of the medial axes—a state-of-the-art report. In: Möller T, Hamann B, Russell RD (eds) Mathematical foundations of scientific visualization, computer graphics, and massive data exploration, mathematics and vizualization. Springer, Berlin, pp 109–125
Siddiqi K, Pizer SM (2008) Medial representations: mathematics, algorithms and applications. Springer, Berlin
Biasotti S, Attali D, Boissonnat JD et al (2008) Keletal structures, shape analysis and structuring, In: De Floriani L, Spagnuolo M (eds) Shape analysis and structuring. Mathematics and visualization. Springer, Berlin, Heidelberg, pp 145–183
Elber G, Cohen E, Drake S (2005) MATHSM: medial axis transform toward high speed machining of pockets. Comput-Aided Des 37(2):241–250
Hanniel I, Elber G (2009) Computing the Voronoi cells of planes, spheres and cylinders in R2. Comput Aided Geom Des 26(6):695–710
Ma J, Choi S (2014) Kinematic skeleton extraction from 3D articulated models. Comput-Aided Des 46(1):221–226
Tanase M, Veltkamp RC (2004) A straight skeleton approximating the medial axis. In: ESA, pp 809–821
Au C (2013) A simple algorithm for medial axis transform computation. Eng Comput 29:139–149
Chen ZC, Fu Q (2014) An efficient, accurate approach to medial axis transforms of pockets with closed free-form boundaries. Eng Comput 30(1):111–123
Dey TK, Zhao W (2004) Approximate medial axis as a Voronoi subcomplex. Comput-Aided Des 36(2):195–202
Choi HI, Choi SW, Moon HP (1997) Mathematical theory of medial axis transform. Pac J Math 181(1):57–88
Lakshmi JK, Punithavalli M (2009) A survey on skeletons in digital image processing. In: International conference on digital image processing, Bangkok, Thailand, March 2007
Lam L, Lee SW, Suen CY (1992) Thinning methodologies—a comprehensive survey. IEEE Trans Pattern Anal Mach Intell 14(9):869–885
Nackman LR (1982) Curvature relations in three-dimensional symmetric axes. Comput Gr Image Process 20:43–57
Scott GL, Turner SC, Zisserman A (1989) Using a mixed wave diffusion process to elicit the symmetry set. Image Vis Comput 7(1):63–70
Siddiqi K, Bouix S, Tannenbaum A et al (1999) The Hamilton–Jacobi skeleton. In: International conference on computer vision (ICCV), pp 828–834
Vleugels J, Overmars M (1995) Approximating generalized Voronoi diagrams in any dimension. Technical report UU-CS-95-14. Department of Computer Science, Utrecht University
Borgefors G, Nyström I, Sanniti di Baja G. (1999) Computing skeletons in three dimensions. Pattern Recognit 32(7):1225–1236
Borgefors G (1996) On digital distance transforms in three dimensions. Comput Vis Image Underst 64(3):368–376
Viswanathan GK, Murugesan A. Nallaperumal K (2013) A parallel thinning algorithm for contour extraction and medial axis transform. In: 2013 IEEE international conference on emerging trends in computing, communication and nanotechnology, ICE-CCN
Stolpner S, Kry P, Siddiqi K (2012) Medial spheres for shape approximation. IEEE Trans Pattern Anal Mach Intell 34(6):1234–1240
Cao TT, Tang K, Mohamed A et al (2010) Parallel Banding Algorithm to compute exact distance transform with the GPU. In: ACM SIGGRAPH symposium on interactive 3D graphics and games, pp 83–90
Jalba AC, Kustra J (2013) A. C. Telea. Surface and curve skeletonization of large 3D models on the GPU. IEEE Trans Pattern Anal Mach Intell 35(6):1495–1508
Ramanathan M, Gurumoorthy B (2005) Constructing medial axis transform of extruded and revolved 3D objects with free-form boundaries. Comput Aided Des 37(13):1370–1387
Chang YC, Kao JH, Pinilla JM, Dong J, Prinz FB (1998) Medial axis transform (MAT) of general 2D shapes and 3D polyhedra for engineering applications. In: The 6th IFIP working conference on geometric modeling: fundamentals and applications, 7–9 Dec 1998, Tokyo, Japan
Sherbrooke EC, Patrikalakis NM, Brisson E (1995) Computation of MA transform of 3-D polyhedral. In: ACM solid modeling, pp 187–199
Aichholzer O, Aigner W, Aurenhammer F et al (2009) Medial axis computation for planar free_form shapes. Comput Aided Des 41:339–349
Meijster A, Roerdin JBTM, Hesselink WH (2000) A general algorithm for computing distance transforms in linear time. In: Goutsias J, Vincent L, Bloomberg DS (eds) Mathematical morphology and its applications to image and signal processing. Computational imaging and vision, vol 18. Springer, Boston, pp 331–340
Hirata T (1996) A unified linear-time algorithm for computing distance maps. Inf Process Lett 58(3):129–133
Ramamurthy R, Farouki T (1999) Voronoi diagram and medial axis algorithm for planar domains with curved boundaries I: theoretical foundations. J Comput Appl Math 102:119–141
Chaussard J, Couprie M, Talbot H (2011) Robust skeletonization using the discrete λ-medial axis. Pattern Recognit Lett 32(9):1384–1394
Miklos B, Giesen J, Pauly M (2010) Discrete scale axis representations for 3D geometry. ACM Trans Gr 29:1–10
Sun F, Choi YK, Yu Y et al (2016) Medial meshes—a compact and accurate representation of medial axis transform. IEEE Trans Visual Comput Gr 22(3):1278–1290
Pan L, Bin W, Feng S et al (2015) Q-MAT: computing medial axis transform by quadratic error minimization. ACM Trans Gr 35(1):8
Piegl LA, Wayne T (1998) Geometry based triangulation of trimmed NURBS surfaces. Comput Aided Des 30(1):11–18
Gao W, Gao SM, Liu SM,YS et al (2006) Multiresolutional similarity assessment andretrieval of solid models based on DBMS. Comput Aided Des 38(9):985–1001
Acknowledgements
The authors appreciate the support from the National Key Technology Support Program (Grant no. 2014BAD04B00), the National Science Foundation of China (Grant nos. 61702074, 61572427 and 61672247), the China Postdoctoral Science Foundation Funded Project (Grant no. 2017M621123) and the Fundamental Research Funds for the Central Universities (Grant nos. 3132017117).
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Zhu, H., Liu, Y., Wang, H. et al. Efficient construction of the medial axis for a CAD model using parallel computing. Engineering with Computers 34, 413–429 (2018). https://doi.org/10.1007/s00366-017-0549-3
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DOI: https://doi.org/10.1007/s00366-017-0549-3