Digimarc Corporation

Robert G Lyons

Ravi K Sharma

John Douglas Lord

Osama M Alattar

Alastair M Reed

John F Stach

Hugh L Brunk

Brett Alan Bradley

Vojtech Holub

Shankar Thagadur Shivappa

Ajith Mulki Kamath

Scott M Long

Aparna R Gurijala

Jacob L Boles

Ammon E Gustafson

Signal processing devices and methods estimate a geometric transform of an image. One method measures correlation between a transformed reference signal component and an image, updates, based on the measured correlation that is below a threshold, coordinates of the reference signal component to a location within a neighborhood around the coordinates of the transformed reference signal component; determines a new geometric transform that transforms the reference signal components to updated coordinates; and applies the new geometric transform to extract encoded digital data from the image.

Signal processors and methods for estimating geometric transformations of images for digital data extraction

Signal processing devices and methods estimate transforms between signals using a least squares technique. From a seed set of transform candidates, a direct least squares method applies a seed transform candidate to a reference signal and then measures correlation between the transformed reference signal and a suspect signal. For each candidate, update coordinates of reference signal features are identified in the suspect signal and provided as input to a least squares method to compute an update to the transform candidate. The method iterates so long as the update of the transform provides a better correlation. At the end of the process, the method identifies a transform or set of top transforms based on a further analysis of correlation, as well as other results.

Signal processors and methods for estimating transformations between signals with least squares

Signal processing devices and methods obtain an estimate of a geometric transform of an image signal, use it to obtain a measure of signal confidence of a reference signal in a sub-block of the image signal, and weight message estimates based on the signal confidence. The geometric transform is used as an approximation of the geometric distortion of an image after digital data is encoded in it, and it is used to compensate for this distortion to facilitate extracting embedded digital messages from the image. Due to the errors in the approximation, the signal confidence metric is determined and used to weight message symbol estimates extracted from the image.

Methods and arrangements involving electronic devices, such as smartphones, tablet computers, wearable devices, etc., are disclosed. One arrangement involves a low-power processing technique for discerning cues from audio input. Another involves a technique for detecting audio activity based on the Kullback-Liebler divergence (KLD) (or a modified version thereof) of the audio input. Still other arrangements concern techniques for managing the manner in which policies are embodied on an electronic device. Others relate to distributed computing techniques. A great variety of other features are also detailed.

Methods and system for cue detection from audio input, low-power data processing and related arrangements

The present disclosure relates generally to digital watermarking and signal encoding. Various colors can be evaluated and modified to carry an encoded or auxiliary signal.

Geometric enumerated watermark embedding for colors and inks

The present disclosure relate generally to digital watermarking and signal encoding. Various colors can be evaluated and modified to carry an encoded or auxiliary signal.

Signal processing devices and methods estimate a geometric transform of an image signal. From a seed set of transform candidates, a method applies a seed transform candidate to a reference signal. For each candidate, update coordinates of reference signal features are identified in the image signal and provided as input to a least squares method to compute an update to the transform candidate. At the end of the process, the method identifies a geometric transform or set of top transforms based on a further analysis of correlation, as well as other results. Phase characteristics are exploited in the process of updating coordinates. The geometric transform is used to facilitate extracting embedded digital messages from the image.

A phase estimation method estimates the phase of signal components using a point spread function. The method obtains a point spread function that expresses complex frequencies at a non integer location in terms of integral frequencies, for a complex frequency of a signal at a non integer location in a complex frequency domain. It obtains complex frequencies of the signal for the integral frequencies, and computes a sum of products of the complex frequencies of the signal at the integral frequencies with the corresponding complex values of the point spread function to provide an estimate of phase of the signal at the non integer location.

Signal processors and methods for estimating transformations between signals with phase estimation

Geometric enumerated watermark embedding for spot colors

The present invention relate generally to digital watermarking spot colors. A process color approximation can be used for a spot color, and chrominance watermarking can be performed to insert a watermark. These techniques are particularly suitable for product packaging, color brochures, etc.

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Portland, OR, United States of America

Robert G Lyons