Image Analysis of Deformable Structures - A Meteorological Example
by Hussein Yahia and Jean-Paul Berroir
The segmentation
of deformable structures is an important task of image analysis. Satellite
image sequences provide a huge amount of data often displaying the temporal
evolution of complex structures, like clouds in the atmosphere on meteorological
data. Structures like clouds and vortices are also subject of fusions,
or can dissolve themselves into many connected components. Powerful deformable
models, like the level-sets methods, are steadily gaining ground in image
analysis and computer vision. In the research conducted in the AIR project
at INRIA-Rocquencourt, a new characterization of level-sets by particle
systems is achieved, leading to models that can be interactively controlled
by an operator and permit the modeling of complex visco-elastic structures
in motion. The control of level-sets by particle systems gives the possibility
of using fast numerical resolution algorithms. It also features the attractive
property of assigning specific internal or external energies to the level-sets,
simply by prescribing particular forces on the finite set of particles.
It also gives the possibility of analyzing motion.
Geostationary satellites may be used to collect input parameters of
meteorological forecast models: winds are computed from the observed clouds
displacements; their estimation is based on the cloud motion analysis at
various altitudes. The study of clouds for themselves, ie their displacement
during their life cycle, is also a very important topic. For instance,
the typical western European climate is dominated by oceanic influences.
Vortex formation over the atlantic ocean is therefore of paramount importance
to weather forecast. It is characterized by a very specific motion: the
cloud structure is winding round its center, yielding a spiral-like shape.
The whole structure also undergoes a fast translation, eastward in the
case of European weather analysis. Another example is found in the Western
African climate, which is influenced by the intertropical convergence area:
it is a location where dry air (trade winds) meet wet air carried by the
African monsoon. This usually generates (in August) a more or less continuous
area of cumulo-nimbuses, that yields approximately 80% of the Sahel and
Sudan water supply. The cloud motion in this area is highly perturbated:
on top of a steady westward translation, intensive activity of clouds causes
them to merge or to break up. Analyzing clouds is then very important for
precipitation forecast. Cloud structures or vortices are deformable structures
subject to large deformations, and their analysis requires the use of segmentation
models allowing topological changes and visco-elastic behaviours.
Among the various deformable models for image segmentation in computer
vision, level-sets methods have drawn particular attention, mainly because
they offer the ability of modeling large deformation, and topological changes.
In the research conducted in the AIR project at INRIA, the level-sets are
represented by particle systems. The implicit function is described by
a finite set of control points, or particles, onto which specific internal
and external energies are assigned to offer a precise control of visco-elastic
behaviours. The internal energy is defined by specific potentials describing
the elastic properties of the level-set. The external energy produces a
force field applied on the particles which attract the level-sets towards
the extracted contour points. Using a particles system leads to fast and
robust minimization techniques, and permits hierarchical refinement. The
global shape is described by few particles, and new control points are
added at specific locations where more precise representation is needed.
The result of the minimization process is an iso-contour whose shape is
interactively manipulable by the user. The implicit function defined this
way can be processed in specific monitoring systems, and the result of
the segmentation can be incorporated in meteorological database systems
to provide specific representation of structures in motion. The use of
dedicated internal energies provide the grounds for the use of these techniques
in various applicative models. This particle system formulation is also
useful for the initialization of the level-set. The use of skeletons and
distance maps provide robust initializations, consistent with affine motion.
Figure 1, 2 and 3 display the result of the segmentation in an image sequence
of cloud structures over Sahel.
Figure 1: Initialisation on the first image of the sequence.
Figure 2: Result of the minimization.
Figure 3: Result on the next image of the sequence.
Image sequence by courtesy of Laboratoire de Meteorologie Dynamique, Ecole
Polytechnique, France.
AIR project is dedicated to the image analysis of satellite data for
environmental problems. The image analysis of natural environmental problem
needs different set of tools that can be applied in different applicative
context. With different studies performed on snakes and level-sets, the
research team is setting up different kinds of segmentation and modeling
tools that are going to be used in different european research contracts
under way. For more information on the AIR project, see: http://www-air.inria.fr
Please contact:
Hussein Yahia - INRIA
Tel: +33 1 3963 5357
E-mail: Hussein.Yahia@inria.fr
