Hewlett-packard Development Company, L.p.

Hewlett-packard Company

Airbus Operations Gmbh

Stephen Bernard Pollard

Steven J Simske

Matthew Donald Gaubatz

Robert Alan Ulichney

Andrew Arthur Hunter

Guy Adams

Maurizio Pilu

David Arthur Grosvenor

Jason S Aronoff

Richard Oliver Kahn

Andrew Clark Goris

Daniel Maack Bloom

Renato Keshet

Jason E Yost

Stephen Philip Cheatle

Marie Vans

George Howell

Oscar A Zuniga

Melvyn Smith

Andrew Hebborn

Lyndon Smith

Shane D Vosa

Hossein Malekmohamadi

Khemraj Emrith

Robert Ulicheny

Faisal Azhar

Alper Oktar

Claus Henrik Pedersen

James Kirrane

An object ID-centered workflow method utilizes an object identifier (ID) associated with an object. Forensic identification of serialization elements of the object ID enables access to a registry of workflows.

Object ID-centered workflow

A method for recovering perspective distortion of a coded dot pattern on a surface, comprises generating a stereo-pair of images of a portion of the coded dot pattern, the stereo-pair of images comprising an overlap region comprising a subset of dots of the coded dot pattern that are common to the stereo-pair of images, selecting, in one image of the stereo-pair of images, a focus pattern from the subset of dots, determining a set of potential matches for the focus pattern in the other image of the stereo-pair of images, for each potential match, determining a set of additional dots of the coded dot pattern consistent with a single plane, and selecting a single plane with the highest number of consistent matched dots.

Recovering perspective distortions

A method is disclosed. The method comprises defining a region of interest on a three-dimensional model of an object. The method may comprise capturing an image of an object manufactured according to the three-dimensional model. The method may comprise determining, using a processor, a position and orientation of the three-dimensional model with respect to the object in the captured image. The method may comprise locating the region of interest on the manufactured object. A portion of the manufactured object within the region of interest may comprise an identifiable feature. An apparatus and a machine-readable medium are also disclosed.

Locating a region of interest on an object

Examples disclosed herein relate to determining image capture position information based on a quasi-periodic pattern. For example, a processor may determine whether a target area is within a captured image based on the detection of a quasi-periodic pattern in a first detection area and in a second detection area of the captured image.

Determine image capture position information based on a quasi-periodic pattern

An example system includes a feature extraction engine. The feature extraction engine is to determine a plurality of scale-dependent features for a portion of a target. The system also includes a signature-generation engine to select a subset of the plurality of scale-dependent features based on a strength of each feature. The signature-generation engine also is to store a numeric representation of the portion of the target and the subset of the plurality of scale-dependent features.

Signature authentications based on features

A data-bearing medium is disclosed. The data-bearing medium includes a section of cells having a set of opposite-shifted clusters. The cells include a combination of opposite shifts of the set of opposite-shifted clusters, which represent a single value.

Data-bearing medium

An example system in accordance with an aspect of the present disclosure includes a halftone engine and a gray value engine. The halftone engine is to apply halftoning to an image recursively across a plurality of levels of image scales and spatial resolutions, to generate a pattern that is at least quasi-periodic across the plurality of levels. The gray value engine is to substitute gray values recursively for at least a portion of the halftoning.

Recursive halftoning and gray value substitution

A system for determining the surface structure of an object, the system comprising a first assembly including an illumination source, and a binary mask to generate a binary pattern, the binary mask disposed between the illumination source and a defocusing element to modify the binary pattern to provide a continuously modulated fringe pattern to illuminate the surface of the object.

Determining surface structures of objects

Digital signature authentication systems and methods are disclosed. An example method of authenticating a digital signature extracted from a high resolution image includes comparing an extracted signature from an image to a reference signature. The example method also includes authenticating the extracted signature against the reference signature according to one of a plurality of different authentication protocols.

Digital signature authentication

A computing system includes a projector, a camera, a calibration target, and a processor. The calibration target has known dimensions and four corners in a fixed position relative to both the projector and the camera. The processor causes the projector to project a calibration image having four corners and a repetitive pattern. The processor further causes the camera to capture a captured image of the calibration image and determine a rotation and translation that brings the four corners of the captured image into correspondence with the four corners of the calibration target and identify internal corner points of the repetitive pattern. The processor further selects an intrinsic parameter value and calibrates a 3D coordinate system of at least one of the camera and the projector to the calibration target using the selected intrinsic parameter value, the rotation and translation, and the internal corner points.

Calibration based on intrinsic parameter selection and a projected calibration target

Examples disclosed herein relate to determining the presence of quasi-periodic two-dimensional object. In one implementation, a processor determines peak points of a DFT of an image where the peak points are points with a value above a threshold relative to surrounding points. The processor may then output information indicating the existence of a quasi-periodic two-dimensional object within the image based on the peak points.

Determine presence of quasi-periodic two-dimensional object

Examples disclosed herein relate to determining peak distances between an origin, point in the frequency domain and peak points of a discrete Fourier transform magnitude of an image of a periodic or quasi-periodic target. In some implementations, a range distance between the target and the imaging lens is determined based on the peak distances.

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Gloucestershire, United Kingdom

Stephen Bernard Pollard