Feature-Sensitive and Adaptive Mesh Generation of Grayscale Images

  • Ming Xu
  • Zhanheng Gao
  • Zeyun Yu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8641)


In the current paper, we present a series of algorithms to generate high quality, feature-sensitive, and adaptive meshes from a given grayscale image. The Canny’s edge detector is employed to guarantee that important image features are preserved in the meshes. A halftoning-based sampling strategy is adopted to provide feature-sensitive and adaptive point distributions in the image domain. A Delaunay-triangulation is used to generate initial triangulation of the image, followed by iterative mesh smoothing for mesh quality improvement. Experimental results on several medical images have shown that the proposed method is effective in producing adaptive meshes with high-quality and well-preserved features.


Mesh generation Feature sensitivity Adaptivity Delaunay triangulation Medical images 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ming Xu
    • 1
  • Zhanheng Gao
    • 2
  • Zeyun Yu
    • 1
  1. 1.Department of Computer ScienceUniversity of WisconsinMilwaukeeUSA
  2. 2.College of Computer Science and TechnologyJilin UniversityChangchunChina

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