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基于貝葉斯模型的骨架裁剪方法

秦紅星 孫穎

秦紅星, 孫穎. 基于貝葉斯模型的骨架裁剪方法[J]. 電子與信息學報, 2015, 37(9): 2069-2075. doi: 10.11999/JEIT150003
引用本文: 秦紅星, 孫穎. 基于貝葉斯模型的骨架裁剪方法[J]. 電子與信息學報, 2015, 37(9): 2069-2075. doi: 10.11999/JEIT150003
Qin Hong-xing, Sun Ying. Approach of Skeleton Pruning with Bayesian Model[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2069-2075. doi: 10.11999/JEIT150003
Citation: Qin Hong-xing, Sun Ying. Approach of Skeleton Pruning with Bayesian Model[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2069-2075. doi: 10.11999/JEIT150003

基于貝葉斯模型的骨架裁剪方法

doi: 10.11999/JEIT150003
基金項目: 

國家自然科學基金青年科學基金(61100113),國家教育部留學歸國基金教外司留 [2012]940號,重慶市首批青年骨干教師項目(渝教人(2011)31號),重慶市基礎與前沿研究計劃項目(cstc2013jcyjA40062),重慶郵電大學學科引進人才基金(A2010-12)和重慶市研究生科研創(chuàng)新項目(CYS14142)

Approach of Skeleton Pruning with Bayesian Model

  • 摘要: 針對大部分骨架計算方法對輪廓噪聲的極端敏感性問題,該文提出一種基于貝葉斯模型的骨架裁剪方法。該方法利用貝葉斯理論對骨架及其生長過程進行建模,進而通過對模型的迭代優(yōu)化實現(xiàn)骨架候選分支的篩選裁剪。由于已有的重建誤差率在分析骨架時不能很好地體現(xiàn)骨架簡潔程度,故該文在骨架重建誤差率的基礎上綜合考慮骨架簡潔度,提出骨架有效率的概念來對骨架做客觀定量分析。實驗結果表明該文算法對輪廓噪聲具有較好的魯棒性,且裁剪出的骨架相比現(xiàn)有算法得到的骨架結構更加簡單,對形狀描述更加準確。
  • Gong Y, Lazebnik S, Gordo A, et al.. Iterative quantization: A procrustean approach to learning binary codes for large-scale image retrieval[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(12): 2916-2929.
    Kim V G, Chaudhuri S, Guibas L, et al.. Shape2pose: Human-centric shape analysis[J]. ACM Transactions on Graphics (TOG), 2014, 33(4): 70-79.
    Huang S S, Shamir A, Shen C H, et al.. Qualitative organization of collections of shapes via quartet analysis[J]. ACM Transactions on Graphics (TOG), 2013, 32(4): 96-96.
    Blum H. Biological shape and visual science (Part I)[J]. Journal of Theoretical Biology, 1973, 38(2): 205-287.
    Xu J. A generalized morphological skeleton transform using both internal and external skeleton points[J]. Pattern Recognition, 2014, 47(8): 2607-2620.
    Song Z, Yu J, Zhou C, et al.. Skeleton correspondence construction and its applications in animation style reusing[J]. Neurocomputing, 2013, 120(10): 461-468.
    Al Nasr K, Liu C, Rwebangira M, et al.. Intensity-based skeletonization of cryoEM gray-scale images using a true segmentation-free algorithm[J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 2013, 10(5): 1289-1298.
    Mayya N and Rajan V T. Voronoi diagrams of polygons: A framework for shape representation[J]. Journal of Mathematical Imaging and Vision, 1996, 6(4): 355-378.
    Daz-Pernil D, Pea-Cantillana F, and Gutirrez-Naranjo M A. Cellular Automata in Image Processing and Geometry[M]. Berlin: Springer International Publishing, 2014: 47-63.
    Choi W P, Lam K M, and Siu W C. Extraction of the Euclidean skeleton based on a connectivity criterion[J]. Pattern Recognition, 2003, 36(3): 721-729.
    Sobiecki A, Yasan H C, Jalba A C, et al.. Mathematical Morphology and Its Applications to Signal and Image Processing[M]. Berlin: Springer International Publishing, 2013: 425-439.
    Babu G R M, Srikrishna A, Challa K, et al.. An error free compression algorithm using morphological decomposition[C]. 2012 International Conference on Recent Advances in Computing and Software Systems (RACSS), Chennai, 2012: 33-36.
    Karimipour F and Ghandehari M. Transactions on Computational Science XX[M]. Berlin: Springer International Publishing, 2013: 138-157.
    Jalba A C, Kustra J, and 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.
    Karimov A, Mistelbauer G, Schmidt J, et al.. ViviSection: skeleton-based volume editing[C]. Computer Graphics Forum, Leipzig, 2013, 32(3pt4): 461-470.
    Cicconet M, Geiger D, Gunsalus K C, et al.. Mirror symmetry histograms for capturing geometric properties in images[C]. 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, 2014: 2981-2986.
    Mokhtarian F and Mackworth A K. A theory of multiscale, curvature-based shape representation for planar curves[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, 14(8): 789-805.
    Ogniewicz R L and Kbler O. Hierarchic voronoi skeletons[J]. Pattern Recognition, 1995, 28(3): 343-359.
    Couprie M, Coeurjolly D, and Zrour R. Discrete bisector function and Euclidean skeleton in 2D and 3D[J]. Image and Vision Computing, 2007, 25(10): 1543-1556.
    Bai X, Latecki L J, and 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.
    Sebastian T B, Klein P N, and Kimia B B. Recognition of shapes by editing their shock graphs[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(5): 550-571.
    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.
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出版歷程
  • 收稿日期:  2015-01-05
  • 修回日期:  2015-05-13
  • 刊出日期:  2015-09-19

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