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Compensated Convex-Based Transforms for Image Processing and Shape Interrogation

In: Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging

Author

Listed:
  • Antonio Orlando

    (Universidad Nacional de Tucumán, CONICET, Departamento de Bioingeniería)

  • Elaine Crooks

    (Swansea University, Department of Mathematics)

  • Kewei Zhang

    (University of Nottingham, School of Mathematical Sciences)

Abstract

This paper reviews some recent applications of the theory of the compensated convex transforms or of the proximity hull as developed by the authors to image processing and shape interrogation with special attention given to the Hausdorff stability and multiscale properties. This paper contains also numerical experiments that demonstrate the performance of our methods compared to the state-of-art ones.

Suggested Citation

  • Antonio Orlando & Elaine Crooks & Kewei Zhang, 2023. "Compensated Convex-Based Transforms for Image Processing and Shape Interrogation," Springer Books, in: Ke Chen & Carola-Bibiane Schönlieb & Xue-Cheng Tai & Laurent Younes (ed.), Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, chapter 51, pages 1827-1886, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-98661-2_106
    DOI: 10.1007/978-3-030-98661-2_106
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