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Weighted Quasi-Interpolant Spline Approximations of Planar Curvilinear Profiles in Digital Images

Author

Listed:
  • Andrea Raffo

    (Istituto di Matematica Applicata e Tecnologie Informatiche “E. Magenes”, Consiglio Nazionale delle Ricerche, Via de Marini 6, 16149 Genoa, Italy)

  • Silvia Biasotti

    (Istituto di Matematica Applicata e Tecnologie Informatiche “E. Magenes”, Consiglio Nazionale delle Ricerche, Via de Marini 6, 16149 Genoa, Italy)

Abstract

The approximation of curvilinear profiles is very popular for processing digital images and leads to numerous applications such as image segmentation, compression and recognition. In this paper, we develop a novel semi-automatic method based on quasi-interpolation. The method consists of three steps: a preprocessing step exploiting an edge detection algorithm; a splitting procedure to break the just-obtained set of edge points into smaller subsets; and a final step involving the use of a local curve approximation, the Weighted Quasi Interpolant Spline Approximation (wQISA), chosen for its robustness to data perturbation. The proposed method builds a sequence of polynomial spline curves, connected C 0 in correspondence of cusps, G 1 otherwise. To curb underfitting and overfitting, the computation of local approximations exploits the supervised learning paradigm. The effectiveness of the method is shown with simulation on real images from various application domains.

Suggested Citation

  • Andrea Raffo & Silvia Biasotti, 2021. "Weighted Quasi-Interpolant Spline Approximations of Planar Curvilinear Profiles in Digital Images," Mathematics, MDPI, vol. 9(23), pages 1-16, November.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:23:p:3084-:d:691677
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    References listed on IDEAS

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    1. Sbibih, D. & Serghini, A. & Tijini, A., 2015. "Superconvergent local quasi-interpolants based on special multivariate quadratic spline space over a refined quadrangulation," Applied Mathematics and Computation, Elsevier, vol. 250(C), pages 145-156.
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