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Shape recognition via an a contrario model for size functions

Abstract : Shape recognition methods are often based on feature comparison. When features are of different natures, combining the value of distances or (dis-)similarity measures is not easy since each feature has its own amount of variability. Statistical models are therefore needed. This article proposes a statistical method, namely an a contrario method, to merge features derived from several families of size functions. This merging is usually achieved through a touchy normalizing of the distances. The proposed model consists in building a probability measure. It leads to a global shape recognition method dedicated to perceptual similarities.
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Conference papers
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Contributor : Frédéric Sur Connect in order to contact the contributor
Submitted on : Thursday, October 5, 2006 - 4:20:52 PM
Last modification on : Thursday, January 20, 2022 - 5:30:25 PM

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Andrea Cerri, Daniela Giorgi, Pablo Musé, Frédéric Sur, Federico Tomassini. Shape recognition via an a contrario model for size functions. 3rd International Conference on Image Analysis and Recognition - ICIAR 2006, Sep 2006, Povoa de Varzim, Portugal. pp.410-421, ⟨10.1007/11867661_37⟩. ⟨inria-00104021⟩



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