Digimarc Corporation

Utkarsh Deshmukh

Geoffrey B Rhoads

Tomas Filler

Ravi K Sharma

John Douglas Lord

Vahid Sedighianaraki

William Y Conwell

Ajith Mulki Kamath

Eric D Evans

Matthew M Weaver

Eliot Rogers

Jerry Allen McMahan, Jr

Arthur L Powell

Christopher A Ambiel

Philip J Stafford

Allison C Sliter

Becky G Kiichle-Gross

Features from a style image are adapted to express a machine-readable code. For example, grains of rice depicted in a style image may be positioned to create a pattern mimicking that of a machine-readable code. The resulting output image can then be used as a graphical component in product packaging (e.g., as a background, border, or pattern fill), while also serving to convey a product identifier to a compliant reader device (e.g., a retail point-of-sale terminal). In some embodiments, a neural network is trained to apply a particular style image to machine readable codes. A great variety of other features and arrangements are also detailed.

Artwork generated to convey digital messages, and methods/apparatuses for generating such artwork

Authenticity of a sticker (e.g., a mark-down sticker on a retail item), or integrity of a closure (e.g., on a delivery bag or package), is confirmed by reference to spatial information. In some embodiments a fingerprint is formed from parameters describing spatial placement of a sticker or pattern on a substrate. In some embodiments a digital watermark pattern provides a spatial frame of reference within which one or more other features can be located. A great many other features and arrangements are also detailed.

Tamper detection arrangements, and point of sales systems employing same

Aspects of the detailed technologies concern training and use of neural networks for fine-grained classification of large numbers of items, e.g., as may be encountered in a supermarket. Mitigating false positive errors is an exemplary area of emphasis. Novel network topologies are also detailed&#x2014;some employing recognition technologies in addition to neural networks. A great number of other features and arrangements are also detailed.

Image processing arrangements

The geometric pose of a patch of watermark data is estimated based on the position of a similar, but non-identical, patch of information within a data structure. The information in the data structure corresponds to a tiled array of calibration patterns that is sampled along at least three non-parallel paths. In a particular embodiment, the calibration patterns are sampled so that edges are globally-curved, yet locally-flat. Use of such information in the data structure enables enhanced pose estimation, e.g., speeding up operation, enabling pose estimation from smaller patches of watermark signals, and/or enabling pose estimation from weaker watermark signals. A great variety of other features and arrangements are also detailed.

Watermark sensing methods and arrangements

The present disclosure relates generally to image signal processing, including encoding signals for image data or artwork. An aggregation module predicts likely detection of an encoded signal, including modeling detection in an environment in which an encoded signal is swiped in front of a camera system comprising at least two cameras.

Aggregating detectability metrics to determine signal robustness

The present disclosure relates to signal decoding and icon (e.g., a logo, shape, icon, etc.) detection. In some implementations, a first response is provided upon signal decoding but no icon detection within first captured image data, and a second response is provided upon signal decoding and icon detection within the first captured image data. Other aspects, combinations and implementations are described as well.

Detection of encoded signals and icons

The present disclosure relates to signal decoding and icon (e.g., a logo, shape, icon, etc.) detection. One aspect includes a method comprising: obtaining an image frame depicting a physical object, the physical object comprising an graphical icon printed thereon, the graphical icon comprising first signal encoding, the physical object comprising second signal encoding that does not overlap the first signal encoding, in which the first signal encoding comprises a first identifier and the second signal encoding comprising a second identifier, in which the first identifier comprises a different identifier relative to the second identifier; analyzing image data associated with the image frame to detect presence of the graphical icon, in which said analyzing determines orientation information associated with the graphical icon; providing the orientation information to an encoded signal detector, the encoded signal detector utilizing the orientation information as a geometric reference to detect the first signal encoding to obtain the first identifier; and using the first identifier, initiating a response for display on a display screen. Other aspects, combinations and implementations are described as well.

Growing community of inventors

Hillsboro, OR, United States of America

Utkarsh Deshmukh