A Fully Automated Method to Detect and Segment a Manufactured Object in an Underwater Color Image

Abstract : In this work we propose a fully automated active contours based method for the detection and the segmentation of a moored manufactured object in an underwater image. Detection of objects in underwater images is difficult due to the variable lighting conditions and shadows on the object. The proposed technique is based on the information contained in the color maps and uses the visual attention method, combined with a statistical approach for the detection and an active contour for the segmentation of the object to overcome the above problems. In the classical active contour method the region descriptor is fixed and the convergence of the method depends on the initialization. With our approach, this dependence is overcome with an initialization using the visual attention results and a criteria to select the best region descriptor. This approach improves the convergence and the processing time while providing the advantages of a fully automated method.
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EURASIP Journal on Advances in Signal Processing, SpringerOpen, 2010, pp.1-10
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Contributeur : Christian Barat <>
Soumis le : jeudi 21 octobre 2010 - 15:00:12
Dernière modification le : lundi 25 octobre 2010 - 08:52:10
Document(s) archivé(s) le : samedi 22 janvier 2011 - 02:51:13

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  • HAL Id : hal-00528288, version 1

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Christian Barat, Ronald Phlypo. A Fully Automated Method to Detect and Segment a Manufactured Object in an Underwater Color Image. EURASIP Journal on Advances in Signal Processing, SpringerOpen, 2010, pp.1-10. <hal-00528288>

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