A Delaunay refinement algorithm for quality 2-dimensional mesh generation
SODA '93 Selected papers from the fourth annual ACM SIAM symposium on Discrete algorithms
Adaptive and quality 3D meshing from imaging data
SM '03 Proceedings of the eighth ACM symposium on Solid modeling and applications
Combining Region Splitting and Edge Detection through Guided Delaunay Image Subdivision
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Imesh: An Image Based Quality Mesh Generation Technique
SIBGRAPI '05 Proceedings of the XVIII Brazilian Symposium on Computer Graphics and Image Processing
Quality meshing of implicit solvation models of biomolecular structures
Computer Aided Geometric Design - Special issue: Applications of geometric modeling in the life sciences
Delaunay refinement algorithms for triangular mesh generation
Computational Geometry: Theory and Applications
A fast approach for accurate content-adaptive mesh generation
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
Generating segmented meshes from textured color images
Journal of Visual Communication and Image Representation
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Techniques devoted to generating triangular meshes from intensity images either take as input a segmented image or generate a mesh without distinguishing individual structures contained in the image. These facts may cause difficulties in using such techniques in some applications, such as numerical simulations. In this work we reformulate a previously developed technique for mesh generation from intensity images called Imesh. This reformulation makes Imesh more versatile due to an unified framework that allows an easy change of refinement metric, rendering it effective for constructing meshes for applications with varied requirements, such as numerical simulation and image modeling. Furthermore, a deeper study about the point insertion problem and the development of geometrical criterion for segmentation is also reported in this paper. Meshes with theoretical guarantee of quality can also be obtained for each individual image structure as a post-processing step, a characteristic not usually found in other methods. The tests demonstrate the flexibility and the effectiveness of the approach.