Quantitative error measures for edge detection

  • Authors:
  • C. Lopez-Molina;B. De Baets;H. Bustince

  • Affiliations:
  • Dpto. Automatica y Computacion, Universidad Publica de Navarra, 31006 Pamplona, Spain and Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9 ...;Department of Mathematical Modeling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Belgium;Dpto. Automatica y Computacion, Universidad Publica de Navarra, 31006 Pamplona, Spain

  • Venue:
  • Pattern Recognition
  • Year:
  • 2013

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Abstract

How to measure the performance of an edge detection method is an open problem. Many performance measures have been presented in the literature. However, there seems to be no agreement on the best option, and there exist no practical studies of the features of some of the most recent measures. In this work we make a comprehensive overview of the different proposals, followed by a practical comparison of the most representative measures on synthetic as well as natural edge images.