Leafsnap: A Computer Vision System for Automatic Plant Species Identification
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.
Cite
Text
Kumar et al. "Leafsnap: A Computer Vision System for Automatic Plant Species Identification." European Conference on Computer Vision, 2012. doi:10.1007/978-3-642-33709-3_36Markdown
[Kumar et al. "Leafsnap: A Computer Vision System for Automatic Plant Species Identification." European Conference on Computer Vision, 2012.](https://mlanthology.org/eccv/2012/kumar2012eccv-leafsnap/) doi:10.1007/978-3-642-33709-3_36BibTeX
@inproceedings{kumar2012eccv-leafsnap,
title = {{Leafsnap: A Computer Vision System for Automatic Plant Species Identification}},
author = {Kumar, Neeraj and Belhumeur, Peter N. and Biswas, Arijit and Jacobs, David W. and Kress, W. John and Lopez, Ida C. and Soares, João V. B.},
booktitle = {European Conference on Computer Vision},
year = {2012},
pages = {502-516},
doi = {10.1007/978-3-642-33709-3_36},
url = {https://mlanthology.org/eccv/2012/kumar2012eccv-leafsnap/}
}