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一種非參數(shù)估計的活動圍道圖像分割方法

楊鴻波,  時永剛,  鄒謀炎

楊鴻波, 時永剛, 鄒謀炎. 一種非參數(shù)估計的活動圍道圖像分割方法[J]. 電子與信息學(xué)報, 2004, 26(12): 1849-1855.
引用本文: 楊鴻波, 時永剛, 鄒謀炎. 一種非參數(shù)估計的活動圍道圖像分割方法[J]. 電子與信息學(xué)報, 2004, 26(12): 1849-1855.
Yang Hong-bo, Shi Yong-gang, Zou Mou-yan. Nonparametric Methods for Image Segmentation Using Active Contour[J]. Journal of Electronics & Information Technology, 2004, 26(12): 1849-1855.
Citation: Yang Hong-bo, Shi Yong-gang, Zou Mou-yan. Nonparametric Methods for Image Segmentation Using Active Contour[J]. Journal of Electronics & Information Technology, 2004, 26(12): 1849-1855.

一種非參數(shù)估計的活動圍道圖像分割方法

Nonparametric Methods for Image Segmentation Using Active Contour

  • 摘要: 該文采用Parzen窗非參數(shù)估計的活動圍道方法進行圖像分割，不必假定圖像區(qū)域符合特定的概率分布，大大增加了該算法的應(yīng)用范圍。通過動態(tài)調(diào)整Parzen窗口參數(shù)，更好地利用了圖像灰度區(qū)域一致的信息，使之更好地適應(yīng)圖像分割的任務(wù)。通過合成圖像和真實圖像的實驗證明此方法具有很好的合理性，具有很好的分割精度和抗噪性能。
    Abstract: This paper applies Parzen-window nonparametric estimation of active contour methods for image segmentation which can be performed without regarding image regions as any of typical probability distributions, so it expands the application range of the algorithm. In order to use the information of gray value congruence in a particular region, the Parzen-window parameter is alterable in estimating the densities. This will be more suit for practical image segmentation. Manj examples of synthetical and real image segmentation prove that the method is rationality, better for curve evolution and has good accuracy and antinoise function.
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  • Terzopoulos D. On matching deformable models to images. Technical Report 60, Schlumberger Palo Alto research, 1986. Reprinted in Topical Meeting on Machine Vision, Technical Digest Series, 1987, Vol.12: 160-167.[2]Kass M, Witkin A, Terzopoulos D. Snakes: active contour models. Intl J. Comp. Vis., 1987,1(4): 321-331.[3]Caselles V, Catte F, Coll T, Dibos F. A geometric model for active contours[J].Numerische Mathematik.1993, 66(1):1-31[4]Malladi R, Sethian J A, Vemuri B C. Shape modeling with front propagation: a level set approach.IEEE Trans. on Part. Anal. Mach. Intell., 1995, PAMI-17(2): 158-175.[5]張麗飛.基于最小描述長度準則的活動圍道方法及相關(guān)技術(shù):[博士論文].北京:中國科學(xué)院電子學(xué)研究所,2002,年11月.[6]Parzen E. On estimation of a probability density function and mode. Annals of Mathematical Static. 1962, 33(3): 1065-1076.[7]Kim Junmo, Fisher Ⅲ W, Yezzi A, Jr., Cetin M, Willsky A S. Nonparametric methods for image segmentation using information theory and curve evolution. IEEE Conf. on Image Processing,Rochester, NY, Sept. 2002, Vol.3: 797-800.[8]張麗飛,王東峰,時永剛,鄒謀炎.基于形變模型的圖像分割技術(shù)綜述[J].電子與信息學(xué)報.2003,25(3):395-403瀏覽[9]Osher S, Sethian J A. Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations[J].J. Computational Physics.1988, 79(1):12-49[10]Sethian J A. Curvature and evolution of fronts[J].Commun. Math. Phys.1985, 101(4):487-499[11]Sethian J A. A review of recent numerical algorithms for hypersurfaces moving with curvature dependent speed. J. Differential Geometry, 1990, 31(1): 131-161.
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出版歷程
  • 收稿日期:  2003-08-11
  • 修回日期:  2004-01-05
  • 刊出日期:  2004-12-19

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