Real-time extraction of connected components in 3-D sonar range images

Auran, Per Gunnar; Malvig, Kjell E.

doi:10.1109/cvpr.1996.517131

Cited by 8 publications

(2 citation statements)

References 7 publications

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“…The coordinates of the targets are identified and highlighted in Figure 4-b. The tracker can then utilize these coordinates and reference [14].…”

Section: The Connected Components Algorithmmentioning

confidence: 99%

Diver detection and tracking with different beamforming algorithms

Sevimli

2023

Signal Processing, Sensor/Information Fusion, and Target Recognition XXXII

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Diver Detection Sonars (DDS) aim to detect the diver and tracking at the specific distance. At the side of signal processing case, there are bunch of beamforming algorithms to localize the target or diver in our case in the literature. In this paper, some beamforming algorithms are combined and compared via PSNR, time each other. Some algorithms show that the effect of sidelobes and reverberation are clearly decreased. Moreover, detection and tracking algorithms are applied to artificial sonar data created with a specific scenario for this purpose.

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“…The coordinates of the targets are identified and highlighted in Figure 4-b. The tracker can then utilize these coordinates and reference [14].…”

Section: The Connected Components Algorithmmentioning

confidence: 99%

Diver detection and tracking with different beamforming algorithms

Sevimli

2023

Signal Processing, Sensor/Information Fusion, and Target Recognition XXXII

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“…A different approach is presented in [2] and [3], in which volumetric data processing is addressed. The work of Auran et al [4,5] proposed the reconstruction problem of sonar data by using an occupancy grid approach proposed in [6] for robotic applications. In this paper, the 3D information is reconstructed from a sequence of images, acquired from different views by conventional high resolution sonar.…”

Section: Introductionmentioning

confidence: 99%

3D reconstruction of seafloor from sonar images based on the multi-sensor method

Sun

Shim

Bai

2008

2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems

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This paper proposes a method to estimate the three dimensional aspects of the seafloor using a sequence of sonar images combing GPS positioning. The sonar images are segmented into three kinds of regions using MRF method: echo, shadow and background. The echo information corresponds to the signal back-scattered by the object located on the seafloor while the shadow is due to the absence of back-scattering from behind the object. The remaining information is the background. The reconstruction scheme processes the echo and shadow information separately. A two-dimensional elevation map is estimated from the shadow information and a two-dimensional reflection map is computed from the echoes. And the final reconstruction result merges both of the two maps. The reconstruction result is presented by the experiments using theMatlab simulation in the end of this paper, which prove this method can be implemented in real time as it reconstruct the 3D information successfully and requires only limited computational resources

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Image Analysis and Computer Vision: 1996

Rosenfeld

1997

Computer Vision and Image Understanding

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Real-time extraction of connected components in 3-D sonar range images

Cited by 8 publications

References 7 publications

Diver detection and tracking with different beamforming algorithms

Diver detection and tracking with different beamforming algorithms

3D reconstruction of seafloor from sonar images based on the multi-sensor method

Image Analysis and Computer Vision: 1996

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