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流域变换算法中过度分割的平滑解决方法 被引量:4

A New Method of Solving Over-Segmentation in Watershed Algorithms
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摘要 流域变换是数学形态学中用于图像分割的经典方法,应用十分广泛,但其过度分割问题一直未得到很好的解决。本文首先介绍了流域变换算法的思想,以及引起过渡分割的原因;然后,提出一种解决过度分割问题的快速方法———平滑算子,并通过理论手段证明了该方法的有效性。实验结果表明,该方法是解决流域分割中过渡分割问题的有效方法。 Watershed transform is a classical and widely used method of image segmentation in mathematical morphology, while over segmentation is an inherent problem of the watershed image segmentation and which has not been solved at present. This paper firstly introduces the watershed segmentation algorithms and their implementations, and the cause of over segmentation is also explained. Then this paper presents a method called smooth operator to solve the over segmentation problem in a fast way. Theoretical and experimental results show that smooth operator is an effective way to solve the over segmentation problem.
出处 《计算机工程与科学》 CSCD 2005年第3期29-31,共3页 Computer Engineering & Science
基金 国家863计划资助项目(2002AA714021 2002AA1Z2101 2002AA104510) 教育部网格项目资助(CG2003 GA00103)
关键词 计算机视觉 计算机图形学 图像分割 流域变换算法 平滑算子 过渡分割 watershed transform image segmentation excessive segmentation smooth operator
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参考文献4

  • 1周海芳,蒋艳凰,杨学军.流域变换建模及其算法研究的新进展[J].中国图象图形学报,2003,9(1):11-17. 被引量:9
  • 2周海芳,蒋艳凰,杨学军.流域变换的串行与并行策略研究[J].国防科技大学学报,2002,24(6):71-76. 被引量:4
  • 3Vincent L,Soille P. Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations[J]. IEEE Trans on Pattern Analysis Machine Intelligence, 1991,13(6):583-598.
  • 4Beucher S,Meyer F. The Morphological Approach to Segmentationation: The Watershed Transformation[A]. E R Dougherty ed. Mathematical Morphology in Image Processing[M]. 1993.433-481.

二级参考文献32

  • 1Beucher S,Meyer F. The Morphological Approach to Segmentation: The Watershed Transformation [C]. In E.R. Dougherty, Editor, Mathematical Morphology in Image Processing, Marcel Dekker Inc., N.Y.,1993:433-481.
  • 2Dobrin B.P,Viero T, et al. Fast Watershed Algorithms: Analysis and Extensions [C]. In Proceedings SPIE Nonlinear Image Processing Ⅴ, San Jose, California, 1994:209-220.
  • 3Meyer F. Integrals and Gradients of Images [C]. In Proceedings SPIE, Image Algebra and Morphological Image Processing Ⅲ, San Diego, California, 1992:200-211.
  • 4Meyer F. Integrals, Gradients and Watershed Lines [C]. Proc. Mathematical Morphology and Its Applications to Signal Processing, Barcelona, May 1993:70-75.
  • 5Meyer F,Beucher S. Morphological Segmentation [J]. Journal of Visual Communication and Image Representation,1990,1(1):21-46.
  • 6Meyer F. Topographic Distance and Watershed Lines [J]. Signal Processing,1994,38:113-125.
  • 7Roerdink J B,Meijster A. The Watershed Transform: Definitions, Algorithms and Strategies [J]. Fundamental Information, 2000,41:187-228.
  • 8Bieniek A,Burkhardt H, et al. A Parallel Watershed Algorithm [C]. In Proc. 10th Scandinavian Conference on Image Analysis (SCIA'97), Lappeenranta, Finland, 1997: 237-244.
  • 9Vincent L, Soille P. Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations [J]. IEEE Trans. Patt. Anal. Mach. Intell. 1991,13(6):583-598.
  • 10Viero T. Algorithms for Image Sequence Filtering, Coding and Image Segmentation [D]. Ph D Thesis, Tampere University of Technology, Tampere, Finland, January 1996.

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