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Linear Symbol Plotting Algorithm Based on Centripetal Catmull-Rom Spline

Published: 01 July 2020 Publication History

Abstract

In order to improve the effect of generating linear symbols in situational plotting, eliminate the "sharp corners" and "self-intersection" that occur in the plotting process, and improve the accuracy of curve fitting, this paper proposes a linear symbol plotting algorithm based on centripetal Catmull-Rom spline curve, and compares the plotting effect of this algorithm with traditional spline curve algorithm. The experimental results prove that compared with the traditional curve plotting algorithm, the proposed algorithm has the characteristics of fewer control points and good fitting effects, which improves the plotting efficiency.

References

[1]
Li, J. C. and Liu, C. Z. 2018. the C3 quasi Catmull-Rom spline function with parameters. J. Math. Num. Sin. 40,1(Feb. 2018), 96--106.
[2]
Chen, H. Q., Li, F. X. and Zhang, Q. Y. 2012 A Progressive Rendering Method for Smooth Trajectories J. Syst. Simu. 24,2(Jan. 2012), 357--360
[3]
Yan, Z. P., et al. 2017 k-Curves: Interpolation at Local Maximum Curvature. 36.4(2017):1--7.
[4]
Tan, J. H. and Acharya, U. R. 2014 Active Spline Model: A Shape Based Model Interactive Segmentation Dig. Sign. Proc. 35, 64--74
[5]
Yuksel, C., Schaefer, S. and Keyser, J. 2011 Parameterization and applications of Catmull--Rom curves Comp. Aid. Desi. 43,7(Aug, 2011), 747--755.

Cited By

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  • (2021)ATDP: An Adaptive Spatio-Temporal Trajectory Clustering Algorithm Based on Density Peak2021 7th International Conference on Computer and Communications (ICCC)10.1109/ICCC54389.2021.9674375(1210-1214)Online publication date: 10-Dec-2021

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  1. Linear Symbol Plotting Algorithm Based on Centripetal Catmull-Rom Spline

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      cover image ACM Other conferences
      ICGDA '20: Proceedings of the 2020 3rd International Conference on Geoinformatics and Data Analysis
      April 2020
      176 pages
      ISBN:9781450377416
      DOI:10.1145/3397056
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      • VIENUT: Vienna University of Technology

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 01 July 2020

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      Author Tags

      1. Catmull-Rom spline
      2. Curve Algorithm
      3. Situational Plotting

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      • (2021)ATDP: An Adaptive Spatio-Temporal Trajectory Clustering Algorithm Based on Density Peak2021 7th International Conference on Computer and Communications (ICCC)10.1109/ICCC54389.2021.9674375(1210-1214)Online publication date: 10-Dec-2021

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