Mine classification using a hybrid set of descriptors

Abstract : This paper is concerned with the problem of recognition of objects laying on the sea-bed. A high resolution sonar provides high-quality acoustic images of the sea-bed, allowing the classification of objects from their cast shadow. After the segmentation step, a set of features is extracted from the shadow. We propose an approach based on a hybrid set of descriptors, combining features of different origins. We first compute topological parameters: the extent and the elongation. In addition to these classical features, affine moment invariants seem suitable for sonar images. Indeed, under weak perspective conditions, the perspective transformation is well approximated by an affine transformation. A four-dimensional vector is then computed characterizing the shadow. The method has been tested on simulated sonar images.
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https://hal-ensta-bretagne.archives-ouvertes.fr/hal-00504822
Contributeur : Isabelle Quidu <>
Soumis le : mercredi 21 juillet 2010 - 15:22:36
Dernière modification le : mercredi 18 décembre 2019 - 17:13:03
Archivage à long terme le : vendredi 22 octobre 2010 - 16:34:29

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Oceans00hybridDescriptors.pdf
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  • HAL Id : hal-00504822, version 1

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Isabelle Quidu, Jean-Philippe Malkasse, Gilles Burel, Pierre Vilbé. Mine classification using a hybrid set of descriptors. IEEE OCEANS'2000, Sep 2000, Providence, Rhode Island, United States. ⟨hal-00504822⟩

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