Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: The disclosure relates to a smartphone-based virtual wallet, that manages payment options available to a user. One claim recites a method employing a user's portable device, the device including a display and a sensor, the method including acts of: initiating a multi-party auction to solicit bids from a plurality of financial vendors to facilitate a financial transaction for the user, the plurality of remotely-located financial vendors being associated with the user via a virtual wallet hosted on the user's portable device; receiving bids from the plurality of financial vendors; presenting a user interface using the display, the user interface identifying at least two bids solicited from the multi-party auction; upon receiving an indication of a user-selected bid from the at least two bids, initiating a financial transaction using at least some of the details in the user selected bid and information obtained from the virtual wallet. A great variety of other features, arrangements and claims are also detailed.

Abstract: 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.