Analysis of buried objects in 3D underwater acoustic images by a volumetric segmentation algorithm

To extract useful information about the buried objects contained in acoustic sub-bottom images a segmentation algorithm is mandatory. The literature on the segmentation of 3D acoustic underwater images is very limited, and, more in general, this task is still considered a challenging problem in comp...

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Bibliographic Details
Published inProceedings of OCEANS 2005 MTS/IEEE pp. 791 - 797 Vol. 1
Main Authors Palmese, M., Trucco, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Acoustical engineering
Algorithm design and analysis
Buried object detection
Computer vision
Data mining
Decision theory
Filtering
Image analysis
Image segmentation
Underwater acoustics
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Summary:To extract useful information about the buried objects contained in acoustic sub-bottom images a segmentation algorithm is mandatory. The literature on the segmentation of 3D acoustic underwater images is very limited, and, more in general, this task is still considered a challenging problem in computer vision. The volumetric segmentation method presented in this paper follows a volume growing approach, essentially a 3D extension to the traditional 2D region growing one. The volume growing operation is guided by a statistical approach based on optimal decision theory. Some pre-processing activities, e.g., filtering and enhancement, mainly aimed at preparing data to obtain good segmentation results, have also been developed.
ISBN:0933957343
9780933957343
ISSN:0197-7385
DOI:10.1109/OCEANS.2005.1639849