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P. Dollár, C. Zitnick. Structured Forests for Fast Edge Detection. International Conference on Computer Vision, 2013.

Dollár and Zitnick (also [1]) propose a commonly used learning approach to edge detection based on structured random forests. The Structured Edge Detection Toolbox is available on GitHub or from Microsoft Research. Note that Dollár's Computer Vision Toolbox may be required. Examples are shown in figure 1. Further, the toolbox also includes an implementation of SLIC Superpixels [2].

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Figure 1 (click to enlarge): Example images from the Berkeley Segmentation Dataset [3] and corresponding edges computed using the Structured Edge Detection Toolbox.
  • [1] P. Dollár, C. Zitnick. Structured Forests for Fast Edge Detection. Computing Research Repository, 2014.
  • [2] R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, S. Süsstrunk. SLIC superpixels. Technical report, École Polytechnique Fédérale de Lausanne, 2010.
  • [3] P. Arbeláez, M. Maire, C. Fowlkes, J. Malik. Contour detection and hierarchical image segmentation. Transactions on Pattern Analysis and Machine Intelligence, volume 33, number 5, pages 898–916, 2011.

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