Data-driven and Automatic Surface Texture Analysis Using Persistent Homology

  title={Data-driven and Automatic Surface Texture Analysis Using Persistent Homology},
  author={Melih C. Yesilli and Firas A. Khasawneh},
  journal={2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA)},
Surface roughness plays an important role in analyzing engineering surfaces. It quantifies the surface topography and can be used to determine whether the resulting surface finish is acceptable or not. Nevertheless, while several existing tools and standards are available for computing surface roughness, these methods rely heavily on user input thus slowing down the analysis and increasing manufacturing costs. Therefore, fast and automatic determination of the roughness level is essential to… 


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