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# Cleaning Sonar Terrain Data - PowerPoint PPT Presentation

Freek van Walderveen Aarhus University. Cleaning Sonar Terrain Data. Blue: reconstructed surface. Green: points removed by both manual cleaning and our algorithm. Red: points kept during manual cleaning, but removed by our algorithm.

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Cleaning Sonar Terrain Data

• Blue: reconstructed surface.

• Green: points removed by both manual cleaning and our algorithm.

• Red: points kept during manual cleaning, but removed by our algorithm.

• Orange: points removed by our algorithm, but kept during manual cleaning.

Real sonar data includes over-hangs: situations where one surface appears above another one, allowing the sonar to obtain points on both surfaces.

In the picture to the right, the orange section of the pipe-line does not lie on the seabed, leaving a gap, such that points on the seabed are also reported.

Top: Cross-section of a pipeline.

Bottom: Same pipeline in perspective.

A pipeline surrounded by two ribbons of struc-tural noise.

Due to the 2D triangulation, the points on the pipe appear in small com-ponents and will be removed early. This problem can be solved by augmenting the triangulated graph.

Red points: overlooked by operator?

Pipeline spanning a valley.

Green points represent noise, removed by both algorithms. Orange points are removed by the origi-nal algorithm, even though they should have been kept, which is what the extended algorithm indeed does.

input point

triangulated surface

projection

to the plane

Noise caused by fish. Overlays show front and back sides of one group of points.

empty circle

MADALGO – Center for Massive Data Algorithmics, a Center of the Danish National Research Foundation