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Memorias de investigación
Artículos en revistas:
A Morphological Approach to Curvature-Based Evolution of Curves and Surfaces
Año:2014
Áreas de investigación
  • Inteligencia artificial
Datos
Descripción
We introduce new results connecting differential and morphological operators that provide a formal and theoretically grounded approach for stable and fast contour evolution. Contour evolution algorithms have been extensively used for boundary detection and tracking in computer vision. The standard solution based on partial differential equations and level-sets requires the use of numerical methods of integration that are costly computationally and may have stability issues. We present a morphological approach to contour evolution based on a new curvature morphological operator valid for surfaces of any dimension. We approximate the numerical solution of the curve evolution PDE by the successive application of a set of morphological operators defined on a binary level-set and with equivalent infinitesimal behavior. These operators are very fast, do not suffer numerical stability issues, and do not degrade the level set function, so there is no need to reinitialize it. Moreover, their implementation is much easier since they do not require the use of sophisticated numerical algorithms. We validate the approach providing a morphological implementation of the geodesic active contours, the active contours without borders, and turbopixels. In the experiments conducted, the morphological implementations converge to solutions equivalent to those achieved by traditional numerical solutions, but with significant gains in simplicity, speed, and stability.
Internacional
Si
JCR del ISI
Si
Título de la revista
Ieee Transactions on Pattern Analysis And Machine Intelligence
ISSN
0162-8828
Factor de impacto JCR
4,795
Información de impacto
Datos JCR del año 2012
Volumen
DOI
Número de revista
Desde la página
2
Hasta la página
17
Mes
ENERO
Ranking
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Pablo Márquez Neila (UPM)
  • Autor: Luis Baumela Molina (UPM)
  • Autor: Luis Álvarez (ULPGC)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Centro o Instituto I+D+i: Centro de tecnología Biomédica CTB
  • Departamento: Inteligencia Artificial
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