Reconnaissance de feuilles d'arbres par fusion de décisions partielles

National audienceDans le cadre du développement d'une application Smartphone destinée à la reconnaissance des espèces d'arbres, une stratégie basée sur des sous-classifieurs a été mise en place pour reconnaître les feuilles à partir des caractéristiques liées à la base, au sommet et au contour. La théorie des fonctions de croyance est appliquée sur la sortie de chaque sous-classifieur afin de raffiner les résultats en diminuant l'effet de l'incertitude qui existe sur les caractéristiques des feuilles. La décision finale sur l'espèce de feuille est prise en transformant la croyance en probabilité pignistique et en accumulant les probabilités issues de chaque sous-classifieur pour chaque espèce. Les résultats démontrent que notre méthode de sous-classification et de décision obtient de bonnes performances

Interprétation des images sismiques : Approche par fusion coopérative

L'interprétation des images sismiques dans le cadre de la prospection pétrolière, est une opération complexe qui nécessite de la part des experts, une connaissance importante. Afin de les aider, une méthode semi-automatique basée sur la fusion d'informations est proposée. Elle permet de traiter un nombre important de données sismiques. La théorie des sous-ensembles flous a été retenue pour modéliser les connaissances exprimées de manière symbolique par les interprètes et les coupler avec les valeurs numériques des attributs issus de l'image. L'interface logicielle réalisée dans la cadre de cette étude permet, de plus, une coopérativité entre l'utilisateur et la machine grâce à cet aspect symbolique. Cette méthode permet ainsi de reproduire rapidement des segmentations de régions complexes

Monotonic additive preference model for 3D fusion system parameters adjustment

International audience3D image interpretation to understand complex phenomenon is achieved thanks to fusion systems having numerous parameters, difficult to adjust. An approximate model is looking for to simulate the 3D fusion process. The problem is described as a ranking problem and three MCDA methods are considered thanks to holistic preference information on a set of reference pictures: The ACUTA method with linear utilities, the ACUTA enriched by the consideration of linearity pieces and the UTA GMS method. Obtained results show the limit of using monotonic additive utilities for such identification problem

Application of quantitative MCDA methods for parameter setting support of an image processing system

International audienceThis paper proposes to use quantitative methods to identify a preference model reflecting the overall satisfaction of the user according to the numerous parameters of a complex fusion system. The studied fusion system is devoted to 3D image interpretation and it works in interaction with experts who have knowledge and experience of the concerned applications. Such a system involves many sub-parts and each of them has many parameters that must be adjusted to obtain interesting detections. The link between the parameters and the overall satisfaction expressed by the experts is a priori unknown and it is a key issue to better interact with the system. After the presentation of the preference model relevance with the problematic, three model identifications (multivariate, UTA+ and MACBETH) are attempted in this paper to find an interesting set of parameters according to the available overall satisfaction. Obtained results show the complexity of this kind of identification, mainly because of the non monotonicity of the parameter utilities

Aggregation Evaluation of a Fusion System Devoted to Image Interpretation

International audienceInformation fusion has been studied in various domains of computer sciences and engineering, and the use of these techniques has known a large increase. Fusion systems have become over time complex systems integrating information extraction, their representations in an appropriate space, their combinations and their interpretations. The performance evaluation of such systems has become a real problem. The choices of methods and parameter values have a significant impact on the quality of the results. A global evaluation of the fused result does not allow the end-users to adjust the numerous parameters. We propose a local approach to evaluate the mission completeness of the subparts of the fusion system. In this paper, we focuse on the formulation of the mission of fusion subparts and we measure their achievement degree. The aim is to provide to the end-users which subpart do not completely achieve the functionality they were designed for

A multi level evaluation for fusion system interaction improvement

International audienceFusion systems for image interpretation are complex systems that involve a complete information treatment chain (from the information extraction to the decision). Local evaluation of all the sub-parts that composed the system is an interesting way to better characterize its behaviour but it generates many numerical indicators. This paper proposes two intermediate evaluations based on the construction of symbolic indicators from the numerical separability indexes. All the available quality information are then used into a progressive dashboard that allows to better interact with the system

Règles de classification avec conjonction d'implications en prémisse

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Towards the Supervision of a Fusion System for 3D Image Interpretation

International audienceThe use of cooperative fusion systems for image interpretation according to expert knowledge has known a wide growth and they now need reliable ways to evaluate their performance. Local evaluation is an interesting way to better characterize the system behaviour and consequently to have information on which subpart needs to be adjusted. A previously proposed local evaluation based on separability indexes, generates many numerical indicators. In this paper we proposes a symbolic representation of these separability index easier to understand by the experts. To overcome the application of a threshold, the uncertainty of the numeric measures is represented thanks to possibility distributions

Matching of multi-resolution image for remote sensing glacier detection

International audienceMulti-resolution images provide a rich source of information but the combination of the data still difficult due to their different characteristics. In this paper, a fusion approach of multi-source data is presented. A common space for information representation is generated by selecting points of interest that are then connected through a Delaunay triangulation. The obtained topology allows the classification of the landforms based on all the available attributes. The approach is illustrated on glacier detection in Alps mountains

A Separability Index Based on Earth Mover's Distance for Local Evaluation of Fusion Systems

International audienceThis paper deals with the uses of the Earth Mover's Distance for local evaluation of fusion system. Local evaluation is an interesting way to better characterize the system behavior and consequently to have information on which subpart needs to be adjusted. The definition of the subpart mission and its measurement are two key points in this problematic. This paper shows that the use of the Earth Mover's Distance for measuring the mission achievement is a more complete mathematical tool. The efficiency of the approach is illustrated on an information fusion system devoted to 3D image analysis