运用图像重构误差控制的骨架简化方法
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摘要
将贝叶斯模型方法运用于基于图像重构误差控制下的骨架简化问题,通过建立平衡算法实现重构精度与骨架简化的平衡统一.在算法的设计中,通过对骨架分支级别的设置,运用重构误差和骨架简洁度两个控制参数以及平衡算法,在骨架主轴的基础上通过添加相关各级别的骨架分支,实现对骨架分支的优选,最终获得图像的最优近似骨架.实验结果表明:本算法对于边界扰动具有较好的鲁棒性,与其它方法相比,本算法复杂度较低,运算速度更快,得到的骨架也更简洁.
Bayesian model method was applied to the skeleton simplification problem based on image reconstruction error control,and the balance unification of accuracy reconstruction and skeleton simplification was realized by establishing balance algorithm.In the design of the algorithm,skeleton branches were optimized by setting the skeleton branch level and adding skeleton branches at relevant levels on the basis of skeleton spindle by using two control parameters of reconstruction error and skeleton brevity and balancing algorithm,finally, the optimal approximate skeleton of the image was obtained.Experimental results show that the proposed algorithm has good robustness to boundary disturbances,and compared with other methods,it is less complex, faster, and the skeleton is simpler.
Bayesian model method was applied to the skeleton simplification problem based on image reconstruction error control,and the balance unification of accuracy reconstruction and skeleton simplification was realized by establishing balance algorithm.In the design of the algorithm,skeleton branches were optimized by setting the skeleton branch level and adding skeleton branches at relevant levels on the basis of skeleton spindle by using two control parameters of reconstruction error and skeleton brevity and balancing algorithm,finally, the optimal approximate skeleton of the image was obtained.Experimental results show that the proposed algorithm has good robustness to boundary disturbances,and compared with other methods,it is less complex, faster, and the skeleton is simpler.
引文
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[5] JALBA A C, KUSTRA J, TELEA A C. Surface and curve skeletonization of large 3D models on the GPU[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2013, 35(6): 1495-1508.
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[7] FELDMAN J,SINGH M.Bayesian estimation of the shape skeleton[J]. PNAS Proceedings of the National Academy of Sciences of the United States of America, 2006, 103: 18014-18019.
[8] SHEN W, BAI X, YANG X W, et al. Skeleton pruning as trade-off between skeleton simplicity and reconstruction error[J]. Science China Information Sciences, 2013, 56(4):1-14.
[9] 秦红星,孙颖.基于贝叶斯模型的骨架剪裁方法[J].电子与信息学报,2015,37(9):2069-2075.
[10] CHOI H, CHOI S, MOON H. Mathematical theory of medial axis transform[J]. Pacific Journal of Mathematics,1997, 181(1): 57-88.
[2] KARIMIPOUR F, GHANDEHARI M. Transactions on Computational Science XX[M]. Berlin:Springer International Publishing, 2013: 138-157.
[3] BAI X, LATECKI L J. Path similarity skeleton graph matching[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008, 30(7): 1282-1292.
[4] BAI X, LATECKI L J, LIU W Y. Skeleton pruning by contour partitioning with discrete curve evolution[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2007, 29(3): 449-462.
[5] JALBA A C, KUSTRA J, TELEA A C. Surface and curve skeletonization of large 3D models on the GPU[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2013, 35(6): 1495-1508.
[6] 李小燕,程显毅. 基于权值的骨架修剪算法[J].计算机工程与设计,2009,30(14):3374-3376.
[7] FELDMAN J,SINGH M.Bayesian estimation of the shape skeleton[J]. PNAS Proceedings of the National Academy of Sciences of the United States of America, 2006, 103: 18014-18019.
[8] SHEN W, BAI X, YANG X W, et al. Skeleton pruning as trade-off between skeleton simplicity and reconstruction error[J]. Science China Information Sciences, 2013, 56(4):1-14.
[9] 秦红星,孙颖.基于贝叶斯模型的骨架剪裁方法[J].电子与信息学报,2015,37(9):2069-2075.
[10] CHOI H, CHOI S, MOON H. Mathematical theory of medial axis transform[J]. Pacific Journal of Mathematics,1997, 181(1): 57-88.