Editing A New Computational Framework For 2D Shape-Enclosing Contours

Title: A New Computational Framework For 2D Shape-Enclosing Contours

Research Question: How can a new computational framework be developed for extracting 2D shape-enclosing contours from discrete two-dimensional data sets, addressing the challenges of contour extraction, displacement, skeleton extraction, continuation, reﬁnement, and simpliﬁcation?

Methodology: The authors present a new framework for contour extraction in two-dimensional discrete data sets. This framework includes algorithms for dilated contour extraction, contour displacement, shape skeleton extraction, contour continuation, shape feature-based contour reﬁnement, and contour simpliﬁcation. Many of these techniques rely on the application of a Delaunay tessellation. The versatility of this toolbox approach is demonstrated through its application to various scientific problems in material science, biology, and heavy ion physics.

Results: The new framework successfully addresses the challenges of contour extraction from discrete two-dimensional data sets. It provides a unified approach for building 2D shape-enclosing contours from various types of data, such as 2D gray-level images and 1+1D hydro dynamic simulation data. The framework's algorithms, including dilated contour extraction, contour displacement, shape skeleton extraction, contour continuation, shape feature-based contour reﬁnement, and contour simpliﬁcation, are applied to scientiﬁc problems in material science, biology, and heavy ion physics.

Implications: The new computational framework for 2D shape-enclosing contours offers a comprehensive solution to the challenges of contour extraction from discrete two-dimensional data sets. It provides a unified approach for building contours from various types of data, making it applicable to a wide range of scientific problems. The framework's techniques, such as dilated contour extraction, contour displacement, shape skeleton extraction, contour continuation, shape feature-based contour reﬁnement, and contour simpliﬁcation, demonstrate the toolbox's flexibility and adaptability to different applications.

Link to Article: https://arxiv.org/abs/0405029v1
Authors: 
arXiv ID: 0405029v1

[[Category:Computer Science]]
[[Category:Contour]]
[[Category:Extraction]]
[[Category:Shape]]
[[Category:Framework]]
[[Category:Data]]