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Leaf segmentation and tracking using probabilistic parametric active contours

Jonas De Vylder UGent, Daniel Ochoa Donoso UGent, Wilfried Philips UGent, Laury Chaerle UGent and Dominique Van Der Straeten UGent (2011) Lecture Notes in Computer Science. 6930. p.75-85
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.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
image analysis, MODEL, active contours, IMAGE SEGMENTATION, segmentation, SNAKES
in
Lecture Notes in Computer Science
Lect. notes comput. sci.
editor
A Gagalowizc and Wilfried Philips UGent
volume
6930
issue title
Computer vision/computer graphics collaboration techniques, Mirage 2011
pages
75 - 85
publisher
Springer
place of publication
Berlin, Germany
conference name
5th International conference on Computer Vision/Computer Graphics Collaboration Techniques and Applications (Mirage 2011)
conference location
Rocquencourt, France
conference start
2011-10-10
conference end
2011-10-12
Web of Science type
Proceedings Paper
Web of Science id
000313551100007
ISSN
0302-9743
ISBN
9783642241352
9783642241369
DOI
10.1007/978-3-642-24136-9_7
language
English
UGent publication?
yes
classification
P1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1224889
handle
http://hdl.handle.net/1854/LU-1224889
date created
2011-05-16 20:52:32
date last changed
2015-06-17 09:34:19
@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},
  keyword      = {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://dx.doi.org/10.1007/978-3-642-24136-9\_7},
  volume       = {6930},
  year         = {2011},
}

Chicago
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. A Gagalowizc and Wilfried Philips, 6930:75–85. Berlin, Germany: Springer.
APA
De Vylder, Jonas, 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). Presented at the 5th International conference on Computer Vision/Computer Graphics Collaboration Techniques and Applications (Mirage 2011), Berlin, Germany: Springer.
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.
MLA
De Vylder, Jonas, Daniel Ochoa Donoso, Wilfried Philips, et al. “Leaf Segmentation and Tracking Using Probabilistic Parametric Active Contours.” Lecture Notes in Computer Science. Ed. A Gagalowizc & Wilfried Philips. Vol. 6930. Berlin, Germany: Springer, 2011. 75–85. Print.