Geometric Feature Extraction by a Multi-Marked Point Process

Florent Lafarge 1 Georgy Gimel'Farb 2 Xavier Descombes 1
1 ARIANA - Inverse problems in earth monitoring
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SIS - Signal, Images et Systèmes
Abstract : This paper presents a new stochastic marked point process for describing images in terms of a finite library of geometric objects. Image analysis based on conventional marked point processes has already produced convincing results but at the expense of parameter tuning, computing time, and model specificity. Our more general multimarked point process has simpler parametric setting, yields notably shorter computing times, and can be applied to a variety of applications. Both linear and areal primitives extracted from a library of geometric objects are matched to a given image using a probabilistic Gibbs model, and a Jump-Diffusion process is performed to search for the optimal object configuration. Experiments with remotely sensed images and natural textures show that the proposed approach has good potential. We conclude with a discussion about the insertion of more complex object interactions in the model by studying the compromise between model complexity and efficiency.
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Article dans une revue
Trans. on Pattern Analysis and Machine Intelligence, IEEE, 2010, 32 (9), 〈10.1109/TPAMI.2009.152〉
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Soumis le : lundi 28 janvier 2013 - 10:16:22
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Florent Lafarge, Georgy Gimel'Farb, Xavier Descombes. Geometric Feature Extraction by a Multi-Marked Point Process. Trans. on Pattern Analysis and Machine Intelligence, IEEE, 2010, 32 (9), 〈10.1109/TPAMI.2009.152〉. 〈inria-00503140〉



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