2009 · 33 citations · 9 references
ComputingComputer ScienceComputer VisionEdge ComputingMachine VisionDigital Image ProcessingEdge DetectionEdge MetricsImage AnalysisSignal Detection TheoryDetectorsEdge Features
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 FAR-measurements in addition to PSNR applied to the edginess maps are defined to assess the performance of edge detection. The R, DS, P and FAR-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.
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Using contours to detect and localize junctions in natural images
Michael Maire, Pablo Arbeláez, Charless C. Fowlkes et al. · 2008 · 405 citations