Software that automatically recognizes surfaces within complex three-dimensional images can benefit petroleum extraction.
The deep cracking faults that lie within the Earth’s crust are significant geologic surfaces for oil exploration and earthquake prediction. A team from KAUST developed an algorithm that smoothly detects faults and other three-dimensional (3-D) surfaces with high computational efficiency even amid noisy and cluttered data sets .
Identifying objects in images using geometric curves is critical to many computer vision applications. One method uses fast marching algorithms that track how interfaces evolve with time from an initial seed point. This technique uses efficient computational routines to expand the seed curve step-by-step until mathematical conditions corresponding to a boundary are met—the steep slope of a cliff, for instance.
Requiring software users to define probable surface boundaries, however, makes it tricky to use fast marching algorithms for complex 3-D problems.
“It’s a challenge to extract a surface from an image volume when the boundary is non-empty and unknown,” explained Ganesh Sundaramoorthi from the University’s Computer, Electrical and Mathematical Science and Engineering Division. “Until now, no algorithm could handle this task.”
Sundaramoorthi and colleague Marei Algarni recently developed software known as SurfCut to solve these issues. The pair realized that for two-dimensional (2-D) objects, a small curve from a seed point can trace out the surface and automatically stop along the boundary. However, performing the equivalent operations in 3-D required a new approach based on topology, or the mathematical descriptions of features that are preserved under deformation.
The new analysis program uses fast marching methods to compute the shortest paths between a seed point and a moving interface. Ridge sets are then computed by retracting the interface until rigid topological features emerge. These features are likely to lie on the surface, and the team’s algorithm extracts them to efficiently determine 3-D surfaces.
“Our idea embeds 3-D curves on the surface as ridges of a moving front, and we watch the curves evolve as the front propagates,” noted Sundaramoorthi. “Ridge sets are difficult to extract from realistic images, which are discrete and noisy, but our algorithm makes this operation feasible.”
To demonstrate the usefulness of SurfCut, the researchers analyzed a series of seismic images and generated new underground 3-D maps with stunning clarity. “Understanding complex fault surfaces can be hard, even for expert geologists,” Sundaramoorthi said. “Our technique allows them to see structures that are impossible to view using 2-D slices, and is really robust against data imperfections. This could directly impact the oil industry.”
 Algarni, M. & Sundaramoorthi, G. SurfCut: Free-boundary surface extraction. European Conference on Computer Vision (ECCV), Springer, October 2016, in press.
Michelle D'Antoni | Research SEA
Stable magnetic bit of three atoms
21.09.2017 | Sonderforschungsbereich 668
Drones can almost see in the dark
20.09.2017 | Universität Zürich
Plants and algae use the enzyme Rubisco to fix carbon dioxide, removing it from the atmosphere and converting it into biomass. Algae have figured out a way to increase the efficiency of carbon fixation. They gather most of their Rubisco into a ball-shaped microcompartment called the pyrenoid, which they flood with a high local concentration of carbon dioxide. A team of scientists at Princeton University, the Carnegie Institution for Science, Stanford University and the Max Plank Institute of Biochemistry have unravelled the mysteries of how the pyrenoid is assembled. These insights can help to engineer crops that remove more carbon dioxide from the atmosphere while producing more food.
A warming planet
Our brains house extremely complex neuronal circuits, whose detailed structures are still largely unknown. This is especially true for the so-called cerebral cortex of mammals, where among other things vision, thoughts or spatial orientation are being computed. Here the rules by which nerve cells are connected to each other are only partly understood. A team of scientists around Moritz Helmstaedter at the Frankfiurt Max Planck Institute for Brain Research and Helene Schmidt (Humboldt University in Berlin) have now discovered a surprisingly precise nerve cell connectivity pattern in the part of the cerebral cortex that is responsible for orienting the individual animal or human in space.
The researchers report online in Nature (Schmidt et al., 2017. Axonal synapse sorting in medial entorhinal cortex, DOI: 10.1038/nature24005) that synapses in...
Whispering gallery mode (WGM) resonators are used to make tiny micro-lasers, sensors, switches, routers and other devices. These tiny structures rely on a...
Using ultrafast flashes of laser and x-ray radiation, scientists at the Max Planck Institute of Quantum Optics (Garching, Germany) took snapshots of the briefest electron motion inside a solid material to date. The electron motion lasted only 750 billionths of the billionth of a second before it fainted, setting a new record of human capability to capture ultrafast processes inside solids!
When x-rays shine onto solid materials or large molecules, an electron is pushed away from its original place near the nucleus of the atom, leaving a hole...
For the first time, physicists have successfully imaged spiral magnetic ordering in a multiferroic material. These materials are considered highly promising candidates for future data storage media. The researchers were able to prove their findings using unique quantum sensors that were developed at Basel University and that can analyze electromagnetic fields on the nanometer scale. The results – obtained by scientists from the University of Basel’s Department of Physics, the Swiss Nanoscience Institute, the University of Montpellier and several laboratories from University Paris-Saclay – were recently published in the journal Nature.
Multiferroics are materials that simultaneously react to electric and magnetic fields. These two properties are rarely found together, and their combined...
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