Digimarc Corporation

David A Cushman

Ravi K Sharma

Brett Alan Bradley

Shankar Thagadur Shivappa

Ajith Mulki Kamath

Yang Bai

Geoffrey B Rhoads

Tony F Rodriguez

William Y Conwell

Trent J Brundage

Tomas Filler

Vojtech Holub

Aparna R Gurijala

Aparna Gurijala

Items are identified in a waste stream for purposes of recycling, using deterministic and/or probabilistic techniques. Imagery of the waste stream from multiple viewpoints permit creation of a 3D depth draped image representation, from which one or more 2D planes can be synthesized. Phase-coherent patches of recoverable encoded data can be identified from among soiled and crumpled object surfaces, and used in combination to recover object identification information. Recognition of certain items can trigger further image processing that is specific to such items. (Detection of a catsup bottle, for example, can trigger image analysis to discern the presence of catsup residue.) Information about recognized objects can be provided to external data customers, e.g., to track grey market diversion of particular products into unlicensed territories. These and other features and advantages, which can be used alone or in combination, are detailed herein.

Information-client server built on a rapid material identification platform

Audio signal processing enhances audio watermark embedding and detecting processes. Audio signal processes include audio classification and adapting watermark embedding and detecting based on classification. Advances in audio watermark design include adaptive watermark signal structure data protocols, perceptual models, and insertion methods. Perceptual and robustness evaluation is integrated into audio watermark embedding to optimize audio quality relative the original signal, and to optimize robustness or data capacity. These methods are applied to audio segments in audio embedder and detector configurations to support real time operation. Feature extraction and matching are also used to adapt audio watermark embedding and detecting.

Multi-mode audio recognition and auxiliary data encoding and decoding

This disclosure relates to advanced signal processing technology including steganographic embedding and digital watermarking. One combination disclosed in the description is an image processing apparatus including: electronic memory for storing an image, in which the image comprises at least a 1D or 2D barcode represented therein and a first encoded signal encoded therein, the 1D or 2D barcode comprising a first plural-bit code and the first encoded signal comprising a second plural-bit code; means for decoding the 1D or 2D barcode from the image to obtain the first plural-bit code; means for analyzing data representing the image to obtain the second plural-bit code from the first encoded signal; means for determining whether the second plural-bit code conflicts with the first plural-bit code; and means for generating a conflict map, the conflict map comprising an identification of a code conflict, and a spatial location of the code conflict relative to the image. Of course, other features and combinations are described as well.

Detecting conflicts between multiple different encoded signals within imagery

Audio watermark encoding methods employ reversing polarity and pairwise embedding. A watermark signal is generated, mapped to pairs of embedding locations and inserted in the members of the pair with reverse polarity. The pairs of embedding locations correspond to adjacent regions or frames in time or frequency domains. A method for controlling an audio output device captures audio from the device, extracts its identity from a watermark, and modifies the operation of the device, e.g. varying watermark strength or audio loudness.

Audio watermark encoding with reversing polarity and pairwise embedding

Growing community of inventors

McMinnville, OR, United States of America

David A Cushman