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Leafsnap: A Computer Vision System for Automatic Plant Species Identification
Neeraj Kumar1, Peter N. Belhumeur2, Arijit Biswas3, David W. Jacobs3, W. John Kress4, Ida C. Lopez4, and João V.B. Soares3
1University of Washington, Seattle, WA, USA
2Columbia University, New York, NY, USA
3University of Maryland, College Park, MD, USA
4National Museum of Natural History, Smithsonian Institution, Washington, DC, USA
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.
LNCS 7573, p. 502 ff.
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© Springer-Verlag Berlin Heidelberg 2012