Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (6A): 220300284-7.doi: 10.11896/jsjkx.220300284

• Software & Interdiscipline • Previous Articles     Next Articles

Visualization of Ocean Data Vector Field Based on Streamline Distance Clustering

WANG Zhen1,2, YANG Zhengwei1, GAO Shunqi1, ZHANG Lei1   

  1. 1 School of Science and Technology,Tianjin University of Finance and Economics,Tianjin 300222,China;
    2 Marine Information Technology Innovation Center,Ministry of Natural Resources,Tianjin 300171,China
  • Online:2023-06-10 Published:2023-06-12
  • About author:WANG Zhen,born in 1981,Ph.D,associate professor,is a member of China Computer Federation.His main research interests include multi-dimensional reconstruction and visualization for application in computed tomography and computer vision.
  • Supported by:
    Open Fund of the Marine Information Technology Innovation Center of the Ministry of Natural Resources(201906) and National Natural Science Foundation of China(62172294).

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Abstract: Streamlines visualization is an important research object of ocean vector field visualization,in which the setting of number and location for streamlines seed points is the basis.The key to the problem,how to eliminate the visual confusion and occlusion caused by multiple streamlines,is the accurate clustering of generated streamlines and the selection of appropriate represen-tative streamlines within the clustering.In this paper,the PDM distance is proposed to be the similarity measurement,then the fine streamline clustering is implemented after once endpoints streamline clustering.The proposed method effectively solves the problem of inaccurate endpoint clustering results and improves the accuracy of streamline clustering.After sort of all the PDM distance within each clustering,we extract midline and two boundary lines to redraw the streamlines,so as to reduce the pheno-menon of visual confusion and occlusion caused by multiple streamlines.For the problem of huge amount of calculation,the MDS algorithm is proposed to reduce dimension and accelerate computing speed.In addition,in order to further accelerate the calculation speed,the critical point detection algorithm is adopted to reduce the time-consuming vortex generation during the process ofstreamline generation.The effectiveness and superiority of our proposed method are verified by using ocean flow field data from China coast,and the drawing effect of streamline is good.

Key words: Clustering, Vector field visualization, Streamline distance

CLC Number: 

  • TP391
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