The University of North Carolina at Chapel Hill

Farms Technology, LLC

Duke University

Daniel Scott Fritsch

Stephen Murray Pizer

Jason G Tatge

Edward L Chaney

Stephen Aylward

Elizabeth Bullitt

Valen E Johnson

Alyson G Wilson

The invention is directed to methods and systems for commodities procurement with concomitant hedging. The invention enables automatic commodity purchase at a desired basis level when a seller's price matches a buyer's basis bid and concomitantly automatically placing an electronic commodities order to hedge the buyer's purchase.

Methods and systems for purchase of commodities

Systems and methods are disclosed for processing tubular objects in multi-dimensional images. The processing includes generating representations of tubular objects which enable subsequent analysis. Systems and methods for processing tubular objects in a multi-dimensional image include establishing a seed points in a multi-dimensional image, searching for an extremum point corresponding to a tubular object having a central curve of intensity extrema, and extracting a one-dimensional central track corresponding to the tubular object and extents corresponding to a plurality of cross-sections along the tubular object. A number of embodiments are presented which apply the systems and methods to a variety of imaging applications.

Systems and methods for tubular object processing

Methods, systems, and computer program products are provided for automatic image recognition of standard shapes which include a core-based deformable loci skeletal grid used to define and represent an object via a model template. The template includes deformable segments, the changes of which are measurable against the deformed model corresponding to an object in a subsequent image. Statistical correlation techniques optimize the match to further refine the shape of the subsequent image.

Image object matching using core analysis and deformable shape loci

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Chapel Hill, NC, United States of America

Daniel Scott Fritsch