An integral curve attribute based flow segmentation View Full Text


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Article Info

DATE

2016-08

AUTHORS

Lei Zhang, Robert S. Laramee, David Thompson, Adrian Sescu, Guoning Chen

ABSTRACT

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. More... »

PAGES

423-436

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12650-015-0336-4

DOI

http://dx.doi.org/10.1007/s12650-015-0336-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1021716889


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