Journal of Visualization

, Volume 19, Issue 3, pp 423–436 | Cite as

An integral curve attribute based flow segmentation

  • Lei Zhang
  • Robert S. Laramee
  • David Thompson
  • Adrian Sescu
  • Guoning ChenEmail author
Regular Paper


We propose a segmentation method for vector fields that employs the accumulated geometric and physical attributes along integral curves to classify their behavior. In particular, we assign to a given spatio-temporal position the attribute value associated with the integral curve initiated at that point. With this attribute information, our segmentation strategy first performs a region classification. Then, connected components are constructed from the derived classification to obtain an initial segmentation. After merging and filtering small segments, we extract and refine the boundaries of the segments. Because points that are correlated by the same integral curve have the same or similar attribute values, the proposed segmentation method naturally generates segments whose boundaries are better aligned with the flow direction. Therefore, additional processing is not required to generate other geometric descriptors within the segmented regions to illustrate the flow behaviors. We apply our method to a number of synthetic and CFD simulation data sets and compare their results with existing methods to demonstrate its effectiveness.

Graphical abstract


Vector field data Integral curves Flow visualization Segmentation 



We thank Jackie Chen, Mathew Maltude, Tino Weinkauf for the data. This research was in part supported by NSF IIS-1352722 and IIS-1065107.


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Copyright information

© The Visualization Society of Japan 2016

Authors and Affiliations

  • Lei Zhang
    • 1
  • Robert S. Laramee
    • 2
  • David Thompson
    • 3
  • Adrian Sescu
    • 3
  • Guoning Chen
    • 1
    Email author
  1. 1.University of HoustonHoustonUSA
  2. 2.Swansea UniversityWalesUK
  3. 3.Mississippi State UniversityMississippi StateUSA

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