Leaf segmentation and tracking using probabilistic parametric active contours
- Author
- Jonas De Vylder (UGent) , Daniel Ochoa Donoso (UGent) , Wilfried Philips (UGent) , Laury Chaerle and Dominique Van Der Straeten (UGent)
- Organization
- Abstract
- Active contours or snakes are widely used for segmentation and tracking. These techniques require the minimization of an energy function, which is generally a linear combination of a data fit term and a regularization term. This energy function can be adjusted to exploit the intrinsic object and image features. This can be done by changing the weighting parameters of the data fit and regularization term. There is, however, no rule to set these parameters optimally for a given application. This results in trial and error parameter estimation. In this paper, we propose a new active contour framework defined using probability theory. With this new technique there is no need for ad hoc parameter setting, since it uses probability distributions, which can be learned from a given training dataset.
- Keywords
- image analysis, MODEL, active contours, IMAGE SEGMENTATION, segmentation, SNAKES
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-1224889
- MLA
- De Vylder, Jonas, et al. “Leaf Segmentation and Tracking Using Probabilistic Parametric Active Contours.” Lecture Notes in Computer Science, edited by A Gagalowizc and Wilfried Philips, vol. 6930, Springer, 2011, pp. 75–85, doi:10.1007/978-3-642-24136-9_7.
- APA
- De Vylder, J., Ochoa Donoso, D., Philips, W., Chaerle, L., & Van Der Straeten, D. (2011). Leaf segmentation and tracking using probabilistic parametric active contours. In A. Gagalowizc & W. Philips (Eds.), Lecture Notes in Computer Science (Vol. 6930, pp. 75–85). https://doi.org/10.1007/978-3-642-24136-9_7
- Chicago author-date
- De Vylder, Jonas, Daniel Ochoa Donoso, Wilfried Philips, Laury Chaerle, and Dominique Van Der Straeten. 2011. “Leaf Segmentation and Tracking Using Probabilistic Parametric Active Contours.” In Lecture Notes in Computer Science, edited by A Gagalowizc and Wilfried Philips, 6930:75–85. Berlin, Germany: Springer. https://doi.org/10.1007/978-3-642-24136-9_7.
- Chicago author-date (all authors)
- De Vylder, Jonas, Daniel Ochoa Donoso, Wilfried Philips, Laury Chaerle, and Dominique Van Der Straeten. 2011. “Leaf Segmentation and Tracking Using Probabilistic Parametric Active Contours.” In Lecture Notes in Computer Science, ed by. A Gagalowizc and Wilfried Philips, 6930:75–85. Berlin, Germany: Springer. doi:10.1007/978-3-642-24136-9_7.
- Vancouver
- 1.De Vylder J, Ochoa Donoso D, Philips W, Chaerle L, Van Der Straeten D. Leaf segmentation and tracking using probabilistic parametric active contours. In: Gagalowizc A, Philips W, editors. Lecture Notes in Computer Science. Berlin, Germany: Springer; 2011. p. 75–85.
- IEEE
- [1]J. De Vylder, D. Ochoa Donoso, W. Philips, L. Chaerle, and D. Van Der Straeten, “Leaf segmentation and tracking using probabilistic parametric active contours,” in Lecture Notes in Computer Science, Rocquencourt, France, 2011, vol. 6930, pp. 75–85.
@inproceedings{1224889, abstract = {{Active contours or snakes are widely used for segmentation and tracking. These techniques require the minimization of an energy function, which is generally a linear combination of a data fit term and a regularization term. This energy function can be adjusted to exploit the intrinsic object and image features. This can be done by changing the weighting parameters of the data fit and regularization term. There is, however, no rule to set these parameters optimally for a given application. This results in trial and error parameter estimation. In this paper, we propose a new active contour framework defined using probability theory. With this new technique there is no need for ad hoc parameter setting, since it uses probability distributions, which can be learned from a given training dataset.}}, author = {{De Vylder, Jonas and Ochoa Donoso, Daniel and Philips, Wilfried and Chaerle, Laury and Van Der Straeten, Dominique}}, booktitle = {{Lecture Notes in Computer Science}}, editor = {{Gagalowizc, A and Philips, Wilfried}}, isbn = {{9783642241352}}, issn = {{0302-9743}}, keywords = {{image analysis,MODEL,active contours,IMAGE SEGMENTATION,segmentation,SNAKES}}, language = {{eng}}, location = {{Rocquencourt, France}}, pages = {{75--85}}, publisher = {{Springer}}, title = {{Leaf segmentation and tracking using probabilistic parametric active contours}}, url = {{http://doi.org/10.1007/978-3-642-24136-9_7}}, volume = {{6930}}, year = {{2011}}, }
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