Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (6A): 764-770.doi: 10.11896/jsjkx.210400050

• Interdiscipline & Application • Previous Articles     Next Articles

Model Medial Axis Generation Method Based on Normal Iteration

ZONG Di-di, XIE Yi-wu   

  1. College of Information Science and Technology,Dalian Maritime University,Dalian,Liaoning 116026,China
  • Online:2022-06-10 Published:2022-06-08
  • About author:ZONG Di-di,born in 1995,postgraduate.Her main research interests include computer-aided design and graphics.
    XIE Yi-wu,born in 1965,associate professor.His main research interests include database and information system,and data mining.
  • Supported by:
    National Science Foundation for Youth(61702074).

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Abstract: As the dimensionality reduction representation of model,the medial axis has been widely used in many engineering fields because of its good performance.At present,the method of generating the medial axis of the model is mainly based on the idea of approximating the medial axis,or the quality of the medial axis is not high,or the calculation time cost is high.As a result,a method of generating model medial axis based on normal iteration is proposed.The normal iteration method first discretizes the model into a triangular mesh model,and then performs GPU parallel tracking calculations based on the definition of the medial axis on the sample points and triangular faces.After multiple normal iterations,the medial axis points corresponding to all sample points are obtained.Finally,connecting the corresponding medial axis points according to the topological connectivity of the sample points to obtain the medial axis of the model.Experiment results show that the method can generate the model medial axis relatively quickly and accurately under different models,which verifies that the method improves the time efficiency and accuracy of the medial axis generation.

Key words: Definition of medial axis, GPU parallel, Iteration, Normal, Quality of medial axis

CLC Number: 

  • TP391.41
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