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Publications sur Reseaux routiers
Résultat de la recherche dans la liste des publications :
3 Articles |
1 - Incorporating generic and specific prior knowledge in a multi-scale phase field model for road extraction from VHR images.
T. Peng et I. H. Jermyn et V. Prinet et J. Zerubia. IEEE Trans. Geoscience and Remote Sensing, 1(2): pages 139--146, juin 2008.
Mots-clés : Zones urbaines denses, Système d'Information Géographique (SIG), Multiscale, Reseaux routiers, Methodes variationnelles, Very high resolution.
Copyright : ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
@ARTICLE{Peng08b,
|
| author |
= |
{Peng, T. and Jermyn, I. H. and Prinet, V. and Zerubia, J.}, |
| title |
= |
{Incorporating generic and specific prior knowledge in a multi-scale phase field model for road extraction from VHR images}, |
| year |
= |
{2008}, |
| month |
= |
{juin}, |
| journal |
= |
{IEEE Trans. Geoscience and Remote Sensing}, |
| volume |
= |
{1}, |
| number |
= |
{2}, |
| pages |
= |
{139--146}, |
| url |
= |
{http://dx.doi.org/10.1109/JSTARS.2008.922318}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/PengetalTGRS08.pdf}, |
| keyword |
= |
{Zones urbaines denses, Système d'Information Géographique (SIG), Multiscale, Reseaux routiers, Methodes variationnelles, Very high resolution} |
| } |
Abstract :
This paper addresses the problem of updating digital road maps in dense urban areas by extracting the main road network from very high resolution (VHR) satellite images. Building on the work of Rochery et al. (2005), we represent the road region as a 'phase field'. In order to overcome the difficulties due to the complexity of the information contained in VHR images, we propose a multi-scale statistical data model. It enables the integration of segmentation results from coarse resolution, which furnishes a simplified representation of the data, and fine resolution, which provides accurate details. Moreover, an outdated GIS digital map is introduced into the model, providing specific prior knowledge of the road network. This new term balances the effect of the generic prior knowledge describing the geometric shape of road networks (i.e. elongated and of low-curvature) carried by a 'phase field higher-order active contour' term. Promising results on QuickBird panchromatic images and comparisons with several other methods demonstrate the effectiveness of our approach. |
|
2 - Higher-Order Active Contour Energies for Gap Closure.
M. Rochery et I. H. Jermyn et J. Zerubia. Journal of Mathematical Imaging and Vision, 29(1): pages 1-20, septembre 2007.
Mots-clés : Gap closure, Ordre superieur, Contour actif, Forme, A priori, Reseaux routiers.
@ARTICLE{Rochery07,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
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{Higher-Order Active Contour Energies for Gap Closure}, |
| year |
= |
{2007}, |
| month |
= |
{septembre}, |
| journal |
= |
{Journal of Mathematical Imaging and Vision}, |
| volume |
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{29}, |
| number |
= |
{1}, |
| pages |
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{1-20}, |
| url |
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{http://dx.doi.org/10.1007/s10851-007-0021-x}, |
| pdf |
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{ftp://ftp-sop.inria.fr/ariana/Articles/2007_Rochery07.pdf}, |
| keyword |
= |
{Gap closure, Ordre superieur, Contour actif, Forme, A priori, Reseaux routiers} |
| } |
Abstract :
One of the main difficulties in extracting line networks from images, and in particular road networks from remote sensing images, is the existence of interruptions in the data caused, for example, by occlusions. These can lead to gaps in the extracted network that do not correspond to gaps in the real network. In this paper, we describe a higher-order active contour energy that in addition to favouring network-like regions, includes a prior term penalizing networks containing ‘nearby opposing extremities’, thereby making gaps in the extracted network less likely. The new energy term causes such extremities to attract one another during gradient descent. They thus move towards one another and join, closing the gap. To minimize the energy, we develop specific techniques to handle the high-order derivatives that appear in the gradient descent equation. We present the results of automatic extraction of networks from real remote-sensing images, showing the ability of the model to overcome interruptions. |
|
3 - Higher Order Active Contours.
M. Rochery et I. H. Jermyn et J. Zerubia. International Journal of Computer Vision, 69(1): pages 27--42, août 2006.
Mots-clés : Contour actif, Forme, Ordre superieur, A priori, Reseaux routiers.
@ARTICLE{mr_ijcv_06,
|
| author |
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{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
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{Higher Order Active Contours}, |
| year |
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{2006}, |
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{International Journal of Computer Vision}, |
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{27--42}, |
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{http://dx.doi.org/10.1007/s11263-006-6851-y}, |
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{ftp://ftp-sop.inria.fr/ariana/Articles/2006_mr_ijcv_06.pdf}, |
| keyword |
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{Contour actif, Forme, Ordre superieur, A priori, Reseaux routiers} |
| } |
Abstract :
We introduce a new class of active contour models that
hold great promise for region and shape modelling, and
we apply a special case of these models to the
extraction of road networks from satellite and aerial
imagery. The new models are arbitrary polynomial
functionals on the space of boundaries, and thus
greatly generalize the linear functionals used in
classical contour energies. While classical energies
are expressed as single integrals over the contour,
the new energies incorporate multiple integrals, and
thus describe long-range interactions between
different sets of contour points. As prior terms, they
describe families of contours that share complex
geometric properties, without making reference to any
particular shape, and they require no pose estimation.
As likelihood terms, they can describe multi-point
interactions between the contour and the data. To
optimize the energies, we use a level set approach.
The forces derived from the new energies are non-local
however, thus necessitating an extension of standard
level set methods. Networks are a shape family of
great importance in a number of applications,
including remote sensing imagery. To model them, we
make a particular choice of prior quadratic energy
that describes reticulated structures, and augment it
with a likelihood term that couples the data at pairs
of contour points to their joint geometry. Promising
experimental results are shown on real images. |
|
 haut de la page
3 Thèses de Doctorat et Habilitations |
1 - New higher-order active contour models, shape priors, and multiscale analysis: their application to road network extraction from very high resolution satellite images.
T. Peng. Thèse de Doctorat, Universite de Nice Sophia Antipolis, novembre 2008.
Mots-clés : Contour actif d'ordre supérieur, Champ de Phase, A priori, Multiresolution, Reseaux routiers, Very high resolution.
Copyright :
@PHDTHESIS{Peng08d,
|
| author |
= |
{Peng, T.}, |
| title |
= |
{New higher-order active contour models, shape priors, and multiscale analysis: their application to road network extraction from very high resolution satellite images}, |
| year |
= |
{2008}, |
| month |
= |
{novembre}, |
| school |
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{Universite de Nice Sophia Antipolis}, |
| pdf |
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{http://tel.archives-ouvertes.fr/tel-00349768/fr/}, |
| keyword |
= |
{Contour actif d'ordre supérieur, Champ de Phase, A priori, Multiresolution, Reseaux routiers, Very high resolution} |
| } |
Résumé :
L'objectif de cette thèse est de développer et de valider des approches robustes d'extraction semi-automatique de réseaux routiers en zone urbaine dense à partir d'images satellitaires optiques à très haute résolution (THR). Nos modèles sont fondés sur une modélisation par champs de phase des contours actifs d'ordre supérieur (CAOS). Le probléme est difficile pour deux raisons principales : les images THR sont intrinsèquement complexes, et certaines zones des réseaux peuvent prendre une topologie arbitraire. Pour remédier à la complexité de l'information contenue dans les images THR, nous proposons une modélisation statistique multi-résolution des données ainsi qu'un modèle multi-résolution contraint a priori. Ces derniers permettent l'intégration des résultats de segmentation de résolution brute et de résolution fine. De plus, dans le cadre particulier de la mise à jour de réseaux routiers, nous présentons un modèle de forme a priori spécifique, dérivé d'une ancienne carte numérique issue d'un SIG. Ce terme spécifique a priori équilibre l'effet de la connaissance a priori générique apportée par le modèle de CAOS, qui décrit la forme géométrique générale des réseaux routiers. Cependant, le modèle classique de CAOS souffre d'une limitation importante : la largeur des branches du réseau est contrainte à d'être similaire au maximum du rayon de courbure des branches du réseau, fournissant ainsi un modèle non satisfaisant dans le cas de réseaux aux branches droites et étroites ou aux branches fortement incurvées et larges. Nous résolvons ce problème en proposant deux nouveaux modèles : l'un contenant un terme additionnel, nonlocal, non-linéaire de CAOS, et l'autre contenant un terme additionnel, nonlocal, linéaire de CAOS. Ces deux termes permettent le contrôle séparé de la largeur et de la courbure des branches, et fournissent une meilleure prolongation pour une même largeur. Le terme linéaire a plusieurs avantages : d'une part il se calcule plus efficacement, d'autre part il peut modéliser plusieurs largeurs de branche simultanément. Afin de remédier à la difficulté du choix des paramètres de ces modèles, nous analysons les conditions de stabilité pour une longue barre d'une largeur donnée décrite par ces énergies, et montrons ainsi comment choisir rigoureusement les paramètres des fonctions d'énergie. Des expériences sur des images satellitaires THR et la comparaison avec d'autres modèles démontrent la supériorité de nos modèles. |
Abstract :
The objective of this thesis is to develop and validate robust approaches for the semi-automatic extraction of road networks in dense urban areas from very high resolution (VHR) optical satellite images. Our models are based on the recently developed higher-order active contour (HOAC) phase field framework. The problem is difficult for two main reasons: VHR images are intrinsically complex and network regions may have arbitrary topology. To tackle the complexity of the information contained in VHR images, we propose a multiresolution statistical data model and a multiresolution constrained prior model. They enable the integration of segmentation results from coarse resolution and fine resolution. Subsequently, for the particular case of road map updating, we present a specific shape prior model derived from an outdated GIS digital map. This specific prior term balances the effect of the generic prior knowledge carried by the HOAC model, which describes the geometric shape of road networks in general. However, the classical HOAC model suffers from a severe limitation: network branch width is constrained to be similar to maximum network branch radius of curvature, thereby providing a poor model of networks with straight narrow branches or highly curved, wide branches. We solve this problem by introducing two new models: one with an additional nonlinear nonlocal HOAC term, and one with an additional linear nonlocal HOAC term. Both terms allow separate control of branch width and branch curvature, and furnish better prolongation for the same width, but the linear term has several advantages: it is more efficient from a computational standpoint, and it is able to model multiple widths simultaneously. To cope with the difficulty of parameter selection of these models, we analyze the stability conditions for a long bar with a given width described by these energies, and hence show how to choose rigorously the parameters of the energy functions. Experiments on VHR satellite images and comparisons with other approaches demonstrate the superiority of our models. |
|
2 - Contours actifs d'ordre supérieur et leur application à la détection de linéiques dans des images de télédétection.
M. Rochery. Thèse de Doctorat, Universite de Nice Sophia Antipolis, Sophia Antipolis, septembre 2005.
Mots-clés : Contour actif, Ordre superieur, Champ de Phase, Reseaux lineiques, Reseaux routiers.
@PHDTHESIS{rochery_these,
|
| author |
= |
{Rochery, M.}, |
| title |
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{Contours actifs d'ordre supérieur et leur application à la détection de linéiques dans des images de télédétection}, |
| year |
= |
{2005}, |
| month |
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{septembre}, |
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{Universite de Nice Sophia Antipolis}, |
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{Sophia Antipolis}, |
| pdf |
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{http://hal.inria.fr/docs/00/04/86/28/PDF/tel-00010631.pdf}, |
| keyword |
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{Contour actif, Ordre superieur, Champ de Phase, Reseaux lineiques, Reseaux routiers} |
| } |
|
3 - Processus ponctuels pour l'extraction de réseaux linéiques dans les images satellitaires et aériennes.
R. Stoica. Thèse de Doctorat, Universite de Nice Sophia Antipolis, février 2001.
Mots-clés : Processus ponctuels marques, Reseaux lineiques, Reseaux routiers, Geometrie stochastique, RJMCMC.
@PHDTHESIS{rs01,
|
| author |
= |
{Stoica, R.}, |
| title |
= |
{Processus ponctuels pour l'extraction de réseaux linéiques dans les images satellitaires et aériennes}, |
| year |
= |
{2001}, |
| month |
= |
{février}, |
| school |
= |
{Universite de Nice Sophia Antipolis}, |
| pdf |
= |
{Theses/These-stoica.pdf}, |
| keyword |
= |
{Processus ponctuels marques, Reseaux lineiques, Reseaux routiers, Geometrie stochastique, RJMCMC} |
| } |
Résumé :
Les réseaux routiers, ou les réseaux hydrographiques, les vaisseaux sanguins ou bien les fissures dans les matériaux sont connus dans la communauté du traitement d'image sous le nom générique de réseaux liné¨iques. La théorie des processus ponctuels marqués est un cadre mathématique rigoureux qui donne la possibilité de modéliser l'image comme un ensemble d'objets en interaction. Les deux idées principales qui ont motivé ce travail sont : ces réseaux sont approchés par de segments de droite connectés, et les réseaux liné¨iques dans une image sont la réalisation d'un processus ponctuel de Gibbs. Le processus ponctuel qui modèlise les réseaux comporte deux composantes. Le premier terme ("Candy" modèle) gère les états et les interactions entre segments : densité, connectivité, alignement et répulsion des segments. L'emplacement du réseau dans l'image est trouvé grâce au second terme, le terme d'attache aux données. Cette composante du modèle est construite à partir de tests d'hypothèses. L'estimateur des réseaux dans l'image est donné par le minimum d'une fonction d'énergie de Gibbs. Pour trouver l'optimum global de cette fonction, nous mettons en {\oe}uvre un algorithme de type recuit simulé qui s'appuie, sur une dynamique de type Monte Carlo par Chaînes de Markov (MCMC) à sauts réversibles. Des résultats sont présentes sur des images aériennes, SPOT et RADAR (RSO). Nous abordons ensuite deux de problèmes ouverts liés au "Candy" modèle, mais d'un interêt théorique général : la convergence d'une dynamique de Monte Carlo à sauts reversibles, et l'estimation des paramètres des processus ponctuels. Une solution à ces problèmes pourrait ouvrir une nouvelle direction dans la recherche de méthodes non-supervisése en traitement d'image. |
Abstract :
Road or hydrographical networks, blood vessels or fissures in materials are all known by the image processing community under the general name of line networks. The theory of point processes is a rigourous mathematical framework which allows us to model an image as a set of interacting objects. The two main ideas which are the basis of this work are : these networks can be considered as connected segments, and the line networks in an image are the realization of a Gibbs point process. The point process used to model the networks has two components. The first one (Candy model) deals with the states and the interaction of the segments : density, connectivity, alignment, attraction and rejection. The location of the network is determined by the second component, the data term. This component is based on hypothesis tests. The network estimator is given by the minimum of a Gibbs energy. We build a simulated annealing algorithm in order to avoid local minima. This algorithm uses reversible jump Monte Carlo Markov Chain (RJMCMC) dynamics. Results are shown on aerial, SPOT and RADAR (SAR) images. Finally, we start a study on two open problems related to the Candy model, but of general theoretical interest : the convergence of a RJMCMC dynamics, and parameter estimation related to point processes. A solution to these problems would give a new direction for the research of unsupervised methods in image processing. |
|
haut de la page
9 Articles de conférence |
1 - An extended phase field higher-order active contour model for networks and its application to road network extraction from VHR satellite images.
T. Peng et I. H. Jermyn et V. Prinet et J. Zerubia. Dans Proc. European Conference on Computer Vision (ECCV), Marseille, France, octobre 2008.
Mots-clés : Dense urban area, Champ de Phase, Reseaux routiers, Methodes variationnelles, Very high resolution.
Copyright :
@INPROCEEDINGS{Peng08c,
|
| author |
= |
{Peng, T. and Jermyn, I. H. and Prinet, V. and Zerubia, J.}, |
| title |
= |
{An extended phase field higher-order active contour model for networks and its application to road network extraction from VHR satellite images}, |
| year |
= |
{2008}, |
| month |
= |
{octobre}, |
| booktitle |
= |
{Proc. European Conference on Computer Vision (ECCV)}, |
| address |
= |
{Marseille, France}, |
| pdf |
= |
{http://link.springer.com/chapter/10.1007%2F978-3-540-88690-7_38}, |
| keyword |
= |
{Dense urban area, Champ de Phase, Reseaux routiers, Methodes variationnelles, Very high resolution} |
| } |
Abstract :
This paper addresses the segmentation from an image of entities that have the form of a 'network', i.e. the region in the image corresponding to the entity is composed of branches joining together at junctions, e.g. road or vascular networks. We present a new phase field higher-order active contour (HOAC) prior model for network regions, and apply it to the segmentation of road networks from very high resolution satellite images. This is a hard problem for two reasons. First, the images are complex, with much 'noise' in the road region due to cars, road markings, etc., while the background is very varied, containing many features that are locally similar to roads. Second, network regions are complex to model, because they may have arbitrary topology. In particular, we address a severe limitation of a previous model in which network branch width was constrained to be similar to maximum network branch radius of curvature, thereby providing a poor model of networks with straight narrow branches or highly curved, wide branches. To solve this problem, we propose a new HOAC prior energy term, and reformulate it as a nonlocal phase field energy. We analyse the stability of the new model, and find that in addition to solving the above problem by separating the interactions between points on the same and opposite sides of a network branch, the new model permits the modelling of two widths
simultaneously. The analysis also fixes some of the model parameters in terms of network width(s). After adding a likelihood energy, we use the model to extract the road network quasi-automatically from pieces of a QuickBird image, and compare the results to other models in the literature. The results demonstrate the superiority of the new model, the importance of strong prior knowledge in general, and of the new term in particular. |
|
2 - Extraction of main and secondary roads in VHR images using a higher-order phase field model.
T. Peng et I. H. Jermyn et V. Prinet et J. Zerubia. Dans Proc. XXI ISPRS Congress, Part A, pages 215-22, Beijing, China, juillet 2008.
Mots-clés : Reseaux routiers, Zones urbaines, Imagerie satellitaire, Segmentation, Modelling, Methodes variationnelles.
Copyright : ISPRS
@INPROCEEDINGS{Peng08a,
|
| author |
= |
{Peng, T. and Jermyn, I. H. and Prinet, V. and Zerubia, J.}, |
| title |
= |
{Extraction of main and secondary roads in VHR images using a higher-order phase field model}, |
| year |
= |
{2008}, |
| month |
= |
{juillet}, |
| booktitle |
= |
{Proc. XXI ISPRS Congress, Part A}, |
| pages |
= |
{215-22}, |
| address |
= |
{Beijing, China}, |
| pdf |
= |
{http://www.isprs.org/proceedings/XXXVII/congress/3_pdf/33.pdf}, |
| keyword |
= |
{Reseaux routiers, Zones urbaines, Imagerie satellitaire, Segmentation, Modelling, Methodes variationnelles} |
| } |
Abstract :
This paper addresses the issue of extracting main and secondary road networks in dense urban areas from very high resolution (VHR, ~0.61m) satellite images. The difficulty with secondary roads lies in the low discriminative power of the grey-level distributions of road regions and the background, and the greater effect of occlusions and other noise on narrower roads. To tackle this problem, we use a previously developed higher-order active contour (HOAC) phase field model and augment it with an additional non-linear nonlocal term. The additional term allows separate control of road width and road curvature; thus more precise prior knowledge can be incorporated, and better road prolongation can be achieved for the same width. Promising results on QuickBird panchromatic images at reduced resolutions and comparisons with other models demonstrate the role and the efficiency of our new model. |
|
3 - A Phase Field Model Incorporating Generic and Specific Prior Knowledge Applied to Road Network Extraction from VHR Satellite Images.
T. Peng et I. H. Jermyn et V. Prinet et J. Zerubia et B. Hu. Dans Proc. British Machine Vision Conference (BMVC), Warwick, UK, septembre 2007.
Mots-clés : Reseaux routiers, Very high resolution, Ordre superieur, Contour actif, Forme, A priori.
@INPROCEEDINGS{Peng07a,
|
| author |
= |
{Peng, T. and Jermyn, I. H. and Prinet, V. and Zerubia, J. and Hu, B.}, |
| title |
= |
{A Phase Field Model Incorporating Generic and Specific Prior Knowledge Applied to Road Network Extraction from VHR Satellite Images}, |
| year |
= |
{2007}, |
| month |
= |
{septembre}, |
| booktitle |
= |
{Proc. British Machine Vision Conference (BMVC)}, |
| address |
= |
{Warwick, UK}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_Peng07a.pdf}, |
| keyword |
= |
{Reseaux routiers, Very high resolution, Ordre superieur, Contour actif, Forme, A priori} |
| } |
Abstract :
We address the problem of updating road maps in dense urban areas by extracting the main road network from a very high resolution (VHR) satellite image. Our model of the region occupied by the road network in the image is innovative. It incorporates three different types of prior geometric knowledge: generic boundary smoothness constraints, equivalent to a standard active contour prior; knowledge of the geometric properties of road networks (i.e. that they occupy regions composed of long, low-curvature segments joined at junctions), equivalent to a higher-order active contour prior; and knowledge of the road network at an earlier date derived from GIS data, similar to other ‘shape priors’ in the literature. In addition, we represent the road network region as a ‘phase field’, which offers a number of important advantages over other region modelling frameworks. All three types of prior knowledge prove important for overcoming the complexity of geometric ‘noise’ in VHR images. Promising results and a comparison with several other techniques demonstrate the effectiveness of our approach. |
|
4 - Indexing Satellite Images with Features Computed from Man-Made Structures on the Earth’s Surface.
A. Bhattacharya et M. Roux et H. Maitre et I. H. Jermyn et X. Descombes et J. Zerubia. Dans Proc. International Workshop on Content-Based Multimedia Indexing, Bordeaux, France, juin 2007.
Mots-clés : Indexation, Reseaux routiers, Semantique, Retrieval, Feature statistics.
@INPROCEEDINGS{Bhattacharya07a,
|
| author |
= |
{Bhattacharya, A. and Roux, M. and Maitre, H. and Jermyn, I. H. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Indexing Satellite Images with Features Computed from Man-Made Structures on the Earth’s Surface}, |
| year |
= |
{2007}, |
| month |
= |
{juin}, |
| booktitle |
= |
{Proc. International Workshop on Content-Based Multimedia Indexing}, |
| address |
= |
{Bordeaux, France}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_Bhattacharya07a.pdf}, |
| keyword |
= |
{Indexation, Reseaux routiers, Semantique, Retrieval, Feature statistics} |
| } |
Abstract :
Indexing and retrieval from remote sensing image databases relies on the extraction of appropriate information from the data about the entity of interest (e.g. land cover type) and on the robustness of this extraction to nuisance variables. Other entities in an image may be strongly correlated with the entity of interest and their properties can therefore be used to characterize this entity. The road network contained in an image is one example. The properties of road networks vary considerably from one geographical environment to another, and they can therefore be used to classify and retrieve such environments. In this paper, we define several such environments, and classify them with the aid of geometrical and topological features computed from the road networks occurring in them. The relative failure of network extraction methods in certain types of urban area obliges us to segment such areas and to add a second set of geometrical and topological features computed from the segmentations. To validate the approach, feature selection and SVM linear kernel classification are performed on the feature set arising from a diverse image database. |
|
5 - Urban road extraction from VHR images using a multiscale image model and a phase field model of network geometry.
T. Peng et I. H. Jermyn et V. Prinet et J. Zerubia. Dans Proc. Urban, Paris, France, avril 2007.
Mots-clés : Reseaux routiers, Very high resolution, Multiscale, Ordre superieur, Contour actif, Forme.
@INPROCEEDINGS{Peng07_urban,
|
| author |
= |
{Peng, T. and Jermyn, I. H. and Prinet, V. and Zerubia, J.}, |
| title |
= |
{Urban road extraction from VHR images using a multiscale image model and a phase field model of network geometry}, |
| year |
= |
{2007}, |
| month |
= |
{avril}, |
| booktitle |
= |
{Proc. Urban}, |
| address |
= |
{Paris, France}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Peng07urban.pdf}, |
| keyword |
= |
{Reseaux routiers, Very high resolution, Multiscale, Ordre superieur, Contour actif, Forme} |
| } |
Abstract :
This paper addresses the problem of automatically
extracting the main road network in a dense urban area from
a very high resolution optical satellite image using a variational
approach. The model energy has two parts: a phase field higherorder
active contour energy that describes our prior knowledge
of road network geometry, i.e. that it is composed of elongated
structures with roughly parallel borders that meet at junctions;
and a multi-scale statistical image model describing the image
we expect to see given a road network. By minimizing the model
energy, an estimate of the road network is obtained. Promising
results on 0.6m QuickBird Panchromatic images are presented,
and future improvements to the models are outlined. |
|
6 - Computing statistics from a graph representation of road networks in satellite images for indexing and retrieval.
A. Bhattacharya et I. H. Jermyn et X. Descombes et J. Zerubia. Dans Proc. compImage, Coimbra, Portugal, octobre 2006.
Mots-clés : Reseaux routiers, Indexation, Semantique, Retrieval, Feature statistics.
@INPROCEEDINGS{bhatta_compimage06,
|
| author |
= |
{Bhattacharya, A. and Jermyn, I. H. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Computing statistics from a graph representation of road networks in satellite images for indexing and retrieval}, |
| year |
= |
{2006}, |
| month |
= |
{octobre}, |
| booktitle |
= |
{Proc. compImage}, |
| address |
= |
{Coimbra, Portugal}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2006_bhatta_compimage06.pdf}, |
| keyword |
= |
{Reseaux routiers, Indexation, Semantique, Retrieval, Feature statistics} |
| } |
Abstract :
Retrieval from remote sensing image archives relies on the
extraction of pertinent information from the data about the entity of interest (e.g. land cover type), and on the robustness of this extraction to nuisance variables (e.g. illumination). Most image-based characterizations are not invariant to such variables. However, other semantic entities in the image may be strongly correlated with the entity of interest and their properties can therefore be used to characterize this entity. Road networks are one example: their properties vary considerably, for example, from urban to rural areas. This paper takes the first steps towards classification (and hence retrieval) based on this idea. We study the dependence of a number of network features on the class of the image ('urban' or 'rural'). The chosen features include measures of the network density, connectedness, and `curviness'. The feature distributions of the two classes are well separated in feature space, thus providing a basis for retrieval. Classification using kernel k-means confirms this conclusion. |
|
7 - Phase field models and higher-order active contours.
M. Rochery et I. H. Jermyn et J. Zerubia. Dans Proc. IEEE International Conference on Computer Vision (ICCV), Beijing, China, octobre 2005.
Mots-clés : Contour actif, Ordre superieur, Forme, Reseaux lineiques, Reseaux routiers, Champ de Phase.
@INPROCEEDINGS{rochery_iccv05,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Phase field models and higher-order active contours}, |
| year |
= |
{2005}, |
| month |
= |
{octobre}, |
| booktitle |
= |
{Proc. IEEE International Conference on Computer Vision (ICCV)}, |
| address |
= |
{Beijing, China}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/rochery_iccv05.pdf}, |
| keyword |
= |
{Contour actif, Ordre superieur, Forme, Reseaux lineiques, Reseaux routiers, Champ de Phase} |
| } |
Abstract :
The representation and modelling of regions is an important topic in computer vision. In this paper, we represent a region via a level set of a `phase field' function. The function is not constrained, eg to be a distance function; nevertheless, phase field energies equivalent to classical active contour energies can be defined. They represent an advantageous alternative to other methods: a linear representation space; ease of implementation (a PDE with no reinitialization); neutral initialization; greater topological freedom. We extend the basic phase field model with terms that reproduce `higher-order active contour' energies, a powerful way of including prior geometric knowledge in the active contour framework via nonlocal interactions between contour points. In addition to the above advantages, the phase field greatly simplifies the analysis and implementation of the higher-order terms. We define a phase field model that favours regions composed of thin arms meeting at junctions, combine this with image terms, and apply the model to the extraction of line networks from remote sensing images. |
|
8 - Gap closure in (road) networks using higher-order active contours.
M. Rochery et I. H. Jermyn et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Singapore, octobre 2004.
Mots-clés : Contour actif, Gap closure, Ordre superieur, Forme, Reseaux routiers.
@INPROCEEDINGS{Rochery04,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Gap closure in (road) networks using higher-order active contours}, |
| year |
= |
{2004}, |
| month |
= |
{octobre}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Singapore}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/rochery_icip04.pdf}, |
| keyword |
= |
{Contour actif, Gap closure, Ordre superieur, Forme, Reseaux routiers} |
| } |
Abstract :
We present a new model for the extraction of networks from images in the presence of occlusions. Such occlusions cause gaps in the extracted network that need to be closed. Using higher-order active contours, which allow the incorporation of sophisticated geometric information, we introduce a new, non-local, `gap closure' force that causes pairs of network extremities that are close together to extend towards one another and join, thus closing the gap
between them. We demonstrate the benefits of the model using the problem of road network extraction, presenting results on aerial images. |
|
9 - Higher Order Active Contours and their Application to the Detection of Line Networks in Satellite Imagery.
M. Rochery et I. H. Jermyn et J. Zerubia. Dans Proc. IEEE Workshop Variational, Geometric and Level Set Methods in Computer Vision, at ICCV, Nice, France, octobre 2003.
Mots-clés : Ordre superieur, Contour actif, Forme, Reseaux routiers, Segmentation, A priori.
@INPROCEEDINGS{Rochery03a,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Higher Order Active Contours and their Application to the Detection of Line Networks in Satellite Imagery}, |
| year |
= |
{2003}, |
| month |
= |
{octobre}, |
| booktitle |
= |
{Proc. IEEE Workshop Variational, Geometric and Level Set Methods in Computer Vision}, |
| address |
= |
{at ICCV, Nice, France}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/rochery_vlsm03.pdf}, |
| keyword |
= |
{Ordre superieur, Contour actif, Forme, Reseaux routiers, Segmentation, A priori} |
| } |
Abstract :
We present a novel method for the incorporation of shape information
into active contour models, and apply it to the extraction
of line networks (e.g. road, water) from satellite imagery.
The method is based on a new class of contour energies.
These energies are quadratic on the space of one-chains
in the image, as opposed to classical energies, which are linear.
They can be expressed as double integrals on the contour,
and thus incorporate non-trivial interactions between
different contour points. The new energies describe families
of contours that share complex geometric properties, without
making reference to any particular shape. Networks fall
into such a family, and to model them we make a particular
choice of quadratic energy whose minima are reticulated.
To optimize the energies, we use a level set approach. The
forces derived from the new energies are non-local however,
thus necessitating an extension of standard level set methods.
Promising experimental results are obtained using real
images. |
|
haut de la page
6 Rapports de recherche et Rapports techniques |
1 - Higher-Order Active Contour Energies for Gap Closure.
M. Rochery et I. H. Jermyn et J. Zerubia. Rapport de Recherche 5717, INRIA, France, octobre 2005.
Mots-clés : Reseaux routiers, Continuity, Gap closure, Ordre superieur, Contour actif, Forme.
@TECHREPORT{RR_5717,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Higher-Order Active Contour Energies for Gap Closure}, |
| year |
= |
{2005}, |
| month |
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{octobre}, |
| institution |
= |
{INRIA}, |
| type |
= |
{Research Report}, |
| number |
= |
{5717}, |
| address |
= |
{France}, |
| url |
= |
{http://hal.inria.fr/inria-00070300/fr/}, |
| pdf |
= |
{https://hal.inria.fr/file/index/docid/70300/filename/RR-5717.pdf}, |
| ps |
= |
{http://hal.inria.fr/docs/00/07/03/00/PS/RR-5717.ps}, |
| keyword |
= |
{Reseaux routiers, Continuity, Gap closure, Ordre superieur, Contour actif, Forme} |
| } |
Résumé :
L'un des principaux problèmes lors de l'extraction de réseaux
linéiques dans des images, et en particulier l'extraction de réseaux
routiers dans des images de télédétection, est l'existence d'interruptions
dans les données, causées, par exemple, par des occultations. Ces
interruptions peuvent mener à des trous dans le réseau extrait qui
n'existent pas dans le réseau réel. Dans ce rapport, nous décrivons une
énergie de contour actif d'ordre supérieur qui, en plus de favoriser les
régions composées de bras fins et connectés entre eux, inclut un terme d'a
priori qui pénalise les configurations du réseau où des extremités proches
et se faisant face apparaissent. L'apparition dans le réseau extrait de ces
configurations est donc moins probable. Si des extremités proches et se
faisant face apparaissent pendant l'évolution par descente de gradient
utilisée pour minimiser l'énergie, le nouveau terme dans l'énergie crée une
attraction entre ces extremités, qui se rapprochent donc l'une de l'autre
et se rejoignent, fermant ainsi le trou entre elles. Pour minimiser
l'énergie, nous développons des techniques spécifiques pour traiter les
derivées d'ordre élevé qui apparaissent dans l'équation de descente de
gradient. Nous présentons des résultats d'extraction automatique de réseaux
routiers à partir d'images de télédétection, montrant ainsi la capacité du
modèle à surmonter les interruptions. |
Abstract :
One of the main difficulties in extracting line networks from
images, and in particular road networks from remote sensing images, is the
existence of interruptions in the data caused, for example, by occlusions.
These can lead to gaps in the extracted network that do not correspond to
gaps in the real network. In this report, we describe a higher-order active
contour energy that in addition to favouring network-like regions composed
of thin arms joining at junctions, also includes a prior term that
penalizes network configurations containing `nearby opposing extremities',
and thereby makes their appearance in the extracted network less likely. If
nearby opposing extremities form during the gradient descent evolution used
to minimize the energy, the new energy term causes the extremities to
attract one another, and hence to move towards one another and join, thus
closing the gap. To minimize the energy, we develop specific techniques to
handle the high-order derivatives that appear in the gradient descent
equation. We present the results of automatic extraction of networks from
real remote-sensing images, showing the ability of the model to overcome
interruptions. |
|
2 - Higher Order Active Contours.
M. Rochery et I. H. Jermyn et J. Zerubia. Rapport de Recherche 5656, INRIA, France, août 2005.
Mots-clés : Contour actif, Ordre superieur, Reseaux routiers, Forme, A priori.
@TECHREPORT{RR_5656,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Higher Order Active Contours}, |
| year |
= |
{2005}, |
| month |
= |
{août}, |
| institution |
= |
{INRIA}, |
| type |
= |
{Research Report}, |
| number |
= |
{5656}, |
| address |
= |
{France}, |
| url |
= |
{https://hal.inria.fr/inria-00070352}, |
| pdf |
= |
{https://hal.inria.fr/file/index/docid/70352/filename/RR-5656.pdf}, |
| ps |
= |
{https://hal.inria.fr/docs/00/07/03/52/PS/RR-5656.ps}, |
| keyword |
= |
{Contour actif, Ordre superieur, Reseaux routiers, Forme, A priori} |
| } |
Résumé :
Nous introduisons une nouvelle classe de contours actifs qui offre des perspectives intéressantes pour la modélisation des régions et des formes, et nous appliquons un cas particulier de ces modèles à l'extraction de réseaux linéiques dans des images satellitaires et aériennes. Les nouveaux modèles sont des fonctionnelles polynômiales arbitraires sur l'espace des contours, et généralisent ainsi les fonctionnelles linéaires utilisées dans les modèles classiques de contours actifs. Alors que les fonctionnelles classiques s'écrivent avec de simples intégrales sur le contour, les nouvelles énergies sont définies comme des intégrales multiples, décrivant ainsi des interactions de longue portée entre les différents ensembles de points du contour. Utilisées comme des termes d'a priori, les fonctionnelles décrivent des familles de contours aux propriétés géométriques complexes, sans faire référence à une forme spécifique et sans nécessiter l'estimation de la position. Utilisées comme des termes d'attache aux données, elles permettent de décrire des interactions multi-points entre le contour et les données. Afin de minimiser ces énergies, nous adoptons la méthodologie des courbes de niveau. Les forces dérivées des énergies sont cependant non locales, et nécessitent une extension des méthodes de courbes de niveau standard. Les réseaux sont une famille de formes d'une grande importance dans de nombreuses applications et en particulier en télédétection. Pour les modéliser, nous faisons un choix particulier d'énergie quadratique qui décrit des structures branchées et nous ajoutons un terme d'attache aux données qui lie les données et la géométrie du contour au niveau des paires de points du contour. Des résultats d'extraction prometteurs sont montrés sur des images réelles. |
Abstract :
We introduce a new class of active contour models that hold great promise for region and shape modelling, and we apply a special case of these models to the extraction of road networks from satellite and aerial imagery. The new models are arbitrary polynomial functionals on the space of boundaries, and thus greatly generalize the linear functionals used in classical contour energies. While classical energies are expressed as single integrals over the contour, the new energies incorporate multiple integrals, and thus describe long-range interactions between different sets of contour points. As prior terms, they describe families of contours that share complex geometric properties, without making reference to any particular shape, and they require no pose estimation. As likelihood terms, they can describe multi-point interactions between the contour and the data. To optimize the energies, we use a level set approach. The forces derived from the new energies are non-local however, thus necessitating an extension of standard level set methods. Networks are a shape family of great importance in a number of applications, including remote sensing imagery. To model them, we make a particular choice of prior quadratic energy that describes reticulated structures, and augment it with a likelihood term that couples the data at pairs of contour points to their joint geometry. Promising experimental results are shown on real images. |
|
3 - A Comparative Study of Point Processes for Line Network Extraction in Remote Sensing.
C. Lacoste et X. Descombes et J. Zerubia. Rapport de Recherche 4516, Inria, France, juillet 2002.
Mots-clés : Geometrie stochastique, Processus ponctuels marques, Reseaux routiers, Reseaux lineiques, RJMCMC.
@TECHREPORT{4516,
|
| author |
= |
{Lacoste, C. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{A Comparative Study of Point Processes for Line Network Extraction in Remote Sensing}, |
| year |
= |
{2002}, |
| month |
= |
{juillet}, |
| institution |
= |
{Inria}, |
| type |
= |
{Research Report}, |
| number |
= |
{4516}, |
| address |
= |
{France}, |
| url |
= |
{http://hal.inria.fr/inria-00072072}, |
| pdf |
= |
{http://hal.inria.fr/docs/00/07/20/72/PDF/RR-4516.pdf}, |
| ps |
= |
{http://hal.inria.fr/docs/00/07/20/72/PS/RR-4516.ps}, |
| keyword |
= |
{Geometrie stochastique, Processus ponctuels marques, Reseaux routiers, Reseaux lineiques, RJMCMC} |
| } |
Résumé :
Nous présentons, dans ce rapport, une étude comparative entre plusieurs modèles d'extraction de réseaux linéiques, issus de la géométrie stochastique. Nous nous pla ons dans le cadre des processus ponctuels marqués spécifiés par une densité par rapport au processus de Poisson homogène. L'objectif de cette étude est de déterminer quelle type de densité a priori est la plus adaptée à cette probématique de détection de réseaux linéiques, et plus particulièrement de réseaux routiers. Nous reprenons le Candy modèle, introduit dans [21] pour l'extraction de réseaux routiers, et nous l'utilisons comme modèle de référence. Ce modèle est basé sur l'idée qu'un réseau routier peut être assimilé à une réalisation d'un processus Markov objet, où les objets correspondent à des segments en interaction. Nous proposons deux variantes de ce modèle qui font intervenir des coefficients mesurant la qualité des interactions entre objets. La première est une généralisation du Candy modèle et la seconde correspond à une adaptation du modèle IDQ, proposé dans [13] pour l'extraction de bâtiments dans les modèles numériques d'élévation. Nous réalisons l'optimisation de chaque modèle par un recuit simulé sur un algorithme MCMC à sauts réversibles. Les résultats expérimentaux obtenus pour les trois modèles, sur des images satellitaires ou aériennes, permettent de vérifier l'intérêt de l'intégration de la qualité des interactions dans la densité a priori. |
Abstract :
We present in this report a comparative study between models of line network extraction, within a stochastic geometry framework. We rely on the theory of marked point processes specified by a density with respect to the uniform Poisson process. We aim to determine which prior density is the most relevant for road network detection. The Candy model, introduced in [21] for the extraction of road networks, is used as a reference model. This model is based on the idea that a road network can be thought of as a realization of a Markov object process, where the objects correspond to interacting line segments. We have developed two variants of this model which use quality coefficients for interactions. The first of these two variants is a generalization of the Candy model and the second one is an adaptation of the IDQ model proposed in [13] for the problem of building extraction from digital elevation models. The optimization is achieved by a simulated annealing with a RJMCMC algorithm. The experimental results, obtained for each model on aerial or satellite images, show the interest of adding quality coefficients for interactions in the prior density. |
|
4 - Local registration and deformation of a road cartographic database on a SPOT satellite image.
G. Rellier et X. Descombes et J. Zerubia. Rapport de Recherche 3939, Inria, mai 2000.
Mots-clés : Champs de Markov, Reseaux routiers.
@TECHREPORT{rel00,
|
| author |
= |
{Rellier, G. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Local registration and deformation of a road cartographic database on a SPOT satellite image}, |
| year |
= |
{2000}, |
| month |
= |
{mai}, |
| institution |
= |
{Inria}, |
| type |
= |
{Research Report}, |
| number |
= |
{3939}, |
| url |
= |
{https://hal.inria.fr/inria-00072711}, |
| pdf |
= |
{https://hal.inria.fr/file/index/docid/72711/filename/RR-3939.pdf}, |
| ps |
= |
{https://hal.inria.fr/docs/00/07/27/11/PS/RR-3939.ps}, |
| keyword |
= |
{Champs de Markov, Reseaux routiers} |
| } |
Résumé :
Dans ce rapport, nous présentons une méthode pour le recalage local d'un réseau cartographique routier sur une image SPOT, reposant sur l'utilisation des champs de Markov sur graphe. Les données image et cartographique étant obtenues par des sources exogènes, elles sont dégradées par du bruit de nature différente. Ce phénomène peut être à l'origine de différences important- es entre les données. De plus, les cartographes peuvent parfois introduire des distortions dans les cartes afin de souligner certains détails que presente la route (lacets d'une route de montagne) : c'est la généralisation. L'algorithme proposé vise à corriger les erreurs dues au bruit et à la généralisation, et à améliorer la précision du tracé des routes. La méthode proposée consiste à transformer la donnée cartographique en un graphe, et ensuite à définir un champ de Markov afin de faire correspondre le graphe et l'image. |
Abstract :
Herein, we propose a local registration method for cartographic road networks on SPOT satellite images based on Markov Random Fields (MRF) on graphs. Since the cartographic and image data are obtained from exogeneous sources, the noises degrading these data are of different nature. This phenomenon can create important differences between the data. In addition, cartographers sometimes introduce distortions, in the so-called generalization process, in the road map in order to emphasize some details of the road (like the bends of a mountain road). The proposed algorithm aims at correcting the error due to noise and generalization, hence increasing the accuracy of the road map. The proposed method consists in translating the cartographic data into a graph model, and then defining a MRF to fit the graph on the image. |
|
5 - A Markov point process for road extraction in remote sensed images.
R. Stoica et X. Descombes et J. Zerubia. Rapport de Recherche 3923, Inria, 2000.
Mots-clés : Geometrie stochastique, Processus ponctuels marques, Candy model, Reseaux routiers, RJMCMC.
@TECHREPORT{rs00,
|
| author |
= |
{Stoica, R. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{A Markov point process for road extraction in remote sensed images}, |
| year |
= |
{2000}, |
| institution |
= |
{Inria}, |
| type |
= |
{Research Report}, |
| number |
= |
{3923}, |
| url |
= |
{https://hal.inria.fr/inria-00072729}, |
| pdf |
= |
{https://hal.inria.fr/file/index/docid/72729/filename/RR-3923.pdf}, |
| ps |
= |
{https://hal.inria.fr/docs/00/07/27/29/PS/RR-3923.ps}, |
| keyword |
= |
{Geometrie stochastique, Processus ponctuels marques, Candy model, Reseaux routiers, RJMCMC} |
| } |
Résumé :
Nous proposons une nouvelle méthode pour extraire les routes dans les images satellitales et aériennes. Notre approche est basée sur la géométrie stochastique et les dynamiques MCMC à saut réversible. Nous considérons que le réseau routier est un réseau fin, et que ce réseau peut être approximé par des segments connectés. Nous construisons un processus ponctuel marqué qui peut simuler et détecter des réseaux fins. La densité de probabilité de ce processus comporte deux termes : le terme d'attache aux données et le terme a priori. Pour former un réseau, les segments doivent être connectés. Nous souhaitons que les segments soient bien alignés et qu'ils ne se superposent pas. Toutes ces contraintes sont prises en compte par le modèle a priori (Candy modèle). L'emplacement du réseau est donné par le terme d'attache aux données. Ce terme est construit à partir des tests d'hypothèses. Notre modèle probabiliste permet de construire le MAP de l'estimateur du réseau linéique. Pour éviter les minima locaux, nous utilisons un algorithme de type recuit simulé, construit sur une dynamique MCMC à sauts réversibles. Nous montrons des résultats sur des images SPOT, ERS et aériennes. |
Abstract :
In this paper we propose a new method to extract roads in remote sensed images. Our approach is based on stochastic geometry theory and reversible jump Monte Carlo Markov Chains dynamic. We consider that roads consist of a thin network in the image. We make the hypothesis that such a network can be approximated by a network composed of connected line segments. We build a marked point process, which is able to simulate and detect thin networks. The segments have to be connected, in order to form a line-netw- ork. Aligned segments are favored whereas superposition is penalized. Those constraints are taken in account by the prior model (Candy model), which is an area-interaction point process.The location of the network and the specifities of a road network in the image are given by the likelihood term. This term is based on statistical hypothesis tests. The proposed probabilistic model yelds a MAP estimator of the road network. In order to avoid local minima, a simulated annealing algorithm, using a reversible jump MCMC dynamic is designed. Results are shown on SPOT, ERS and aerial images. |
|
6 - Mise en correspondance et recalage de graphes : application aux réseaux routiers extraits d'un couple carte/image.
C. Hivernat et X. Descombes et S. Randriamasy et J. Zerubia. Rapport de Recherche 3529, Inria, octobre 1998.
Mots-clés : Champs de Markov, Reseaux routiers, Correspondance de graphes.
@TECHREPORT{hiv98,
|
| author |
= |
{Hivernat, C. and Descombes, X. and Randriamasy, S. and Zerubia, J.}, |
| title |
= |
{Mise en correspondance et recalage de graphes : application aux réseaux routiers extraits d'un couple carte/image}, |
| year |
= |
{1998}, |
| month |
= |
{octobre}, |
| institution |
= |
{Inria}, |
| type |
= |
{Research Report}, |
| number |
= |
{3529}, |
| url |
= |
{https://hal.inria.fr/inria-00073156}, |
| pdf |
= |
{https://hal.inria.fr/file/index/docid/73156/filename/RR-3529.pdf}, |
| ps |
= |
{https://hal.inria.fr/docs/00/07/31/56/PS/RR-3529.ps}, |
| keyword |
= |
{Champs de Markov, Reseaux routiers, Correspondance de graphes} |
| } |
Résumé :
Nous considérons le problème de la mise en correspondance du réseau routier extrait d'une image SPOT avec celui fourni par une base de données cartographi- que. Cette mise en correspondance comprend deux étapes principales fondées sur des modélisations markoviennes. Dans la première étape, les pixels de l'image sont appariés aux segments cartographiques. Le résultat de cette étape permet de découper le réseau obtenu sur l'image sous forme de chaînes. Ces chaînes sont ensuite mises en correspondance avec les segments cartographiques. Pour finir, une étape de qualification des résultats permet de fournir les primitives fiables afin d'affiner le recalage initial. En bouclant l'algorithme sur la mise en correspondance nous obtenons un processus itératif permettant d'améliorer à la fois le recalage et la mise en correspondance. La qualification automatique des résultats est également une aide à l'interprétation pour la mise à jour cartographique. |
Abstract :
We consider herein the matching problem between the road network extracted from a SPOT image and the roads contained in a cartographic database. This matching consists of two main steps based on a Markovian modelling. During the first step, the image road pixels are associated to the map segments. the derived result allows us to split the image network into chains. These chains are matched with the map segments. Finally, an automatic validation procedure provides matched chains/segments which are used to improve the initial registration. An iterative scheme is obtained by performin- g a new matching. The automatic result validation is also helpful for map updating. |
|
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Article de collection ou Chapitre de livre |
1 - An application of marked point process to the extraction of linear networks for images.
R. Stoica et X. Descombes et M.N.M. Van Lieshout et J. Zerubia. Dans Spatial statitics through applications, Publ. WITPress, 2002.
Mots-clés : Reseaux lineiques, Reseaux routiers, Extraction d'objets, Imagerie satellitaire, Processus ponctuels marques.
@INCOLLECTION{stoicaXDlivre,
|
| author |
= |
{Stoica, R. and Descombes, X. and Van Lieshout, M.N.M. and Zerubia, J.}, |
| title |
= |
{An application of marked point process to the extraction of linear networks for images}, |
| year |
= |
{2002}, |
| booktitle |
= |
{Spatial statitics through applications}, |
| publisher |
= |
{WITPress}, |
| url |
= |
{http://www.witpress.com/books/978-1-85312-649-9}, |
| pdf |
= |
{http://oai.cwi.nl/oai/asset/10645/10645A.pdf}, |
| keyword |
= |
{Reseaux lineiques, Reseaux routiers, Extraction d'objets, Imagerie satellitaire, Processus ponctuels marques} |
| } |
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