A new methodology for evaluation of edge detectors

  • Authors:

  • Rodrige Moreno;Domenec Puig;Carme Julià;Miguel Angel Garcia

  • Affiliations:

  • Rovira i Virgili University, Intelligent Robotics and Computer Vision Group, Dept. of Computer Science and Mathematics, Tarragona, Spain;Rovira i Virgili University, Intelligent Robotics and Computer Vision Group, Dept. of Computer Science and Mathematics, Tarragona, Spain;Rovira i Virgili University, Intelligent Robotics and Computer Vision Group, Dept. of Computer Science and Mathematics, Tarragona, Spain;Autonomous University of Madrid, Dept. of Informatics Engineering, Madrid, Spain

  • Venue:
  • ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
  • Year:
  • 2009

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Abstract

This paper defines a new methodology for evaluating edge detectors through measurements on edginess maps instead of on binary edge maps as previous methodologies do. These measurements avoid possible bias introduced by the application-dependent process of generating binary edge maps from edginess maps. The features of completeness, discriminability, precision and robustness, which a general-purpose edge detector must comply with, are introduced. The R, DS, P and F A R-measurements in addition to P S N R applied to the edginess maps are defined to assess the performance of edge detection. The R, DS, P and F A R-measurements can be seen as generalizations of previously proposed measurements on binary edge maps. Well-known and state-of-the-art edge detectors have been compared by means of the new proposed metrics. Results show that it is difficult for an edge detector to comply with all the proposed features.