Leafsnap: a computer vision system for automatic plant species identification

  • Authors:

  • Neeraj Kumar;Peter N. Belhumeur;Arijit Biswas;David W. Jacobs;W. John Kress;Ida C. Lopez;João V. B. Soares

  • Affiliations:

  • University of Washington, Seattle, WA;Columbia University, New York, NY;University of Maryland, College Park, MD;University of Maryland, College Park, MD;National Museum of Natural History, Smithsonian Institution, Washington, DC;National Museum of Natural History, Smithsonian Institution, Washington, DC;University of Maryland, College Park, MD

  • Venue:
  • ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
  • Year:
  • 2012

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Abstract

We describe the first mobile app for identifying plant species using automatic visual recognition. The system --- called Leafsnap --- identifies tree species from photographs of their leaves. Key to this system are computer vision components for discarding non-leaf images, segmenting the leaf from an untextured background, extracting features representing the curvature of the leaf's contour over multiple scales, and identifying the species from a dataset of the 184 trees in the Northeastern United States. Our system obtains state-of-the-art performance on the real-world images from the new Leafsnap Dataset --- the largest of its kind. Throughout the paper, we document many of the practical steps needed to produce a computer vision system such as ours, which currently has nearly a million users.