Abstract
In this paper we present a system for tree leaf segmentation in natural images that combines a first, unrefined segmentation step, with an estimation of descriptors depicting the general shape of a simple leaf. It is based on a light polygonal model, built to represent most of the leaf shapes, that will be deformed to fit the leaf in the image. Avoiding some classic obstacles of active contour models, this approach gives promising results, even on complex natural photographs, and constitutes a solid basis for a leaf recognition process.
This work has been supported by the French National Agency for Research with the reference ANR-10-CORD-005 (REVES project).
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Nilsback, M.E., Zisserman, A.: Delving into the whorl of flower segmentation. In: British Machine Vision Conference, vol. 1, pp. 570–579 (2007)
Saitoh, T., Kaneko, T.: Automatic recognition of blooming flowers. In: International Conference on Pattern Recognition, vol. 1, pp. 27–30 (2004)
Wang, Z., Chi, Z., Feng, D., Wang, Q.: Leaf image retrieval with shape features. In: Laurini, R. (ed.) VISUAL 2000. LNCS, vol. 1929, pp. 477–487. Springer, Heidelberg (2000)
Wang, X.F., Huang, D.S., Du, J.X., Huan, X., Heutte, L.: Classification of plant leaf images with complicated background. Applied Mathematics and Computation 205, 916–926 (2008)
Belhumeur, P., Chen, D., Feiner, S., Jacobs, D., Kress, W., Ling, H., Lopez, I., Ramamoorthi, R., Sheorey, S., White, S., Zhang, L.: Searching the world’s herbaria: A system for visual identication of plant species. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part IV. LNCS, vol. 5305, pp. 116–129. Springer, Heidelberg (2008)
Mokhtarian, F., Abbasi, S.: Matching shapes with self-intersections: Application to leaf classification. IEEE Transactions on Image Processing 13, 653–661 (2004)
Teng, C.H., Kuo, Y.T., Chen, Y.S.: Leaf segmentation, its 3d position estimation and leaf classification from a few images with very close viewpoints. In: Kamel, M., Campilho, A. (eds.) ICIAR 2009. LNCS, vol. 5627, pp. 937–946. Springer, Heidelberg (2009)
Manh, A.G., Rabatel, G., Assemat, L., Aldon, M.J.: Weed leaf image segmentation by deformable templates. Journal of Agricultural Engineering Research 80, 139–146 (2001)
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active contour models. International Journal of Computer Vision 1, 321–331 (1988)
Chan, T., Vese, L.: Active contours without edges. IEEE Transactions on Image Processing 10, 266–277 (2001)
Unal, G., Yezzi, A., Krim, H.: Information-theoretic active polygons for unsupervised texture segmentation. International Journal of Computer Vision 62, 199–220 (2005)
Yuille, A., Hallinan, P., Cohen, D.: Feature extraction from faces using deformable templates. International Journal of Computer Vision 8, 99–111 (1992)
Felzenszwalb, P.: Representation and detection of deformable shapes. PAMI 27, 208–220 (2004)
Cremers, D., Tischhuser, F., Weickert, J., Schnrr, C.: Diffusion snakes: introducing statistical shape knowledge into the mumford-shah functional. Journal of Computer Vision 50, 295–313 (2002)
Coste, H.: Flore descriptive et illustrée de la France de la Corse et des contrées limitrophes (1906)
Mille, J.: Narrow band region-based active contours and surfaces for 2d and 3d segmentation. Computer Vision and Image Understanding 113, 946–965 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cerutti, G., Tougne, L., Vacavant, A., Coquin, D. (2011). A Parametric Active Polygon for Leaf Segmentation and Shape Estimation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2011. Lecture Notes in Computer Science, vol 6938. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24028-7_19
Download citation
DOI: https://doi.org/10.1007/978-3-642-24028-7_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24027-0
Online ISBN: 978-3-642-24028-7
eBook Packages: Computer ScienceComputer Science (R0)