Edge detection techniques using nonlinear diffusion-based models

Authors

  • Tudor Barbu Institute of Computer Science of the Romanian Academy, Iasi Branch, Romania

DOI:

https://doi.org/10.31926/but.mif.2023.3.65.1.15

Keywords:

edge detection, partial differential equation, anisotropic diffusion model, total variation regularization, multi-scale analysis

Abstract

An overview of the edge detection techniques based on partial differential equations (PDE) is presented in this work. Nonlinear anisotropic diffusion-based boundary extraction approaches, like the influential Perona- Malik model and some improved variants of it, are described first. Anisotropic diffusion-based detection schemes using the mean curvature motion and nonlinear PDE-based approaches combining anisotropic diffusion to the bilateral filter are then discussed here. Some nonlinear reaction-diffusion-based edge detection methods are described next. Variational edge detection solutions using the total variation (TV) regularization or combining the anisotropic diffusion to the TV-based models are then presented. Directional diffusion-based image edge extraction algorithms are also discussed. Our own contributions in this computer vision domain are finally described.

Author Biography

Tudor Barbu, Institute of Computer Science of the Romanian Academy, Iasi Branch, Romania

The Academy of Romanian Scientists

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Published

2023-07-03

Issue

Section

COMPUTER SCIENCE