by Peter Horvath, Ian Jermyn, Zoltan Kato, Josiane Zerubia
Abstract:
A central task in image processing is to find the region in the image corresponding to an entity. In a number of problems, the region takes the form of a collection of circles, e.g. tree crowns in remote sensing imagery; cells in biological and medical imagery. In [1], a model of such regions, the 'gas of circles' model, was developed based on higher-order active contours, a recently developed framework for the inclusion of prior knowledge in active contour energies. However, the model suffers from a defect. In [1], the model parameters were adjusted so that the circles were local energy minima. Gradient descent can become stuck in these minima, producing phantom circles even with no supporting data. We solve this problem by calculating, via a Taylor expansion of the energy, parameter values that make circles into energy inflection points rather than minima. As a bonus, the constraint halves the number of model parameters, and severely constrains one of the two that remain, a major advantage for an energy-based model. We use the model for tree crown extraction from aerial images. Experiments show that despite the lack of parametric freedom, the new model performs better than the old, and much better than a classical active contour.
Reference:
Peter Horvath, Ian Jermyn, Zoltan Kato, Josiane Zerubia, An improved `gas of circles' higher-order active contour model and its application to tree crown extraction, In Proceedings of Indian Conference on Computer Vision, Graphics and Image Processing (Prem Kalra, Shmuel Peleg, eds.), volume 4338 of Lecture Notes in Computer Science, Madurai, India, pp. 152-161, 2006, Springer.
Bibtex Entry:
@string{icvgip="Proceedings of Indian Conference on Computer Vision, Graphics and Image Processing"}
@string{lncs="Lecture Notes in Computer Science"}
@string{springer="Springer"}
@InProceedings{Horvath-etal2006a,
author = {Peter Horvath and Ian Jermyn and Zoltan Kato and
Josiane Zerubia},
title = {An improved `gas of circles' higher-order active
contour model and its application to tree crown
extraction},
booktitle = icvgip,
pages = {152--161},
year = 2006,
editor = {Prem Kalra and Shmuel Peleg},
volume = 4338,
series = lncs,
address = {Madurai, India},
month = dec,
publisher = springer,
pdf = {papers/icvgip2006.pdf},
abstract = {A central task in image processing is to find the
region in the image corresponding to an entity. In a
number of problems, the region takes the form of a
collection of circles, e.g. tree crowns in remote
sensing imagery; cells in biological and medical
imagery. In [1], a model of such regions, the 'gas
of circles' model, was developed based on
higher-order active contours, a recently developed
framework for the inclusion of prior knowledge in
active contour energies. However, the model suffers
from a defect. In [1], the model parameters were
adjusted so that the circles were local energy
minima. Gradient descent can become stuck in these
minima, producing phantom circles even with no
supporting data. We solve this problem by
calculating, via a Taylor expansion of the energy,
parameter values that make circles into energy
inflection points rather than minima. As a bonus,
the constraint halves the number of model
parameters, and severely constrains one of the two
that remain, a major advantage for an energy-based
model. We use the model for tree crown extraction
from aerial images. Experiments show that despite
the lack of parametric freedom, the new model
performs better than the old, and much better than a
classical active contour.}
}