Digimarc Corporation

Adnan M Alattar

Geoffrey B Rhoads

Ravi K Sharma

Osama M Alattar

Tony F Rodriguez

Vojtech Holub

Eliot Rogers

Jun Tian

Brett Alan Bradley

Hugh L Brunk

Tomas Filler

John F Stach

Farid Ahmed

Alastair M Reed

Bruce L Davis

William Y Conwell

Joel R Meyer

Eugene Ted Lin

Robert Craig Brandis

Mehmet Utku Celik

Jerrine K Owen

John A Scriven

Kenneth Lee Levy

J Scott Carr

Brett T Hannigan

Neil E Lofgren

Phillip Andrew Seder

Vahid Sedighianaraki

Joshua V Aller

Gilbert B Shaw

Eric E Ellingson

Reed R Stager

John Kennedy Barr

Robert Durst

A waste stream is analyzed and sorted to segregate different items for recycling. Certain features of the technology improve the accuracy with which waste stream items are diverted to collection repositories. Other features concern adaptation of neural networks in accordance with context information sensed from the waste. Still other features serve to automate and simplify maintenance of machine vision systems used in waste sorting. Yet other aspects of the technology concern marking 2D machine readable code data on items having complex surfaces (e.g., food containers with integral ribbing for structural strength or juice pooling), to mitigate issues that such surfaces can introduce in code reading. Still other aspects of the technology concern prioritizing certain blocks of conveyor belt imagery for analysis. Yet other aspects of the technology concern joint use of near infrared spectroscopy, artificial intelligence, digital watermarking, and/or other techniques, for waste sorting. A variety of further features and arrangements are also detailed.

Methods and arrangements to aid recycling

Watermarking media content, in combination with blockchain and distributed storage networks, prevents the proliferation of Deepfake content. Digital watermarks are embedded in the audio and video tracks of video clips of trusted content producers at the time the videos are captured or before they are distributed. The watermarks are detected at the social media network's portals, nodes, and back ends. The embedded watermark imparts a unique identifier to the video, that links it to a blockchain. The watermarks also allow video source tracking, integrity verification, and alteration localization. The watermark detectors can be standalone software applications, or they can be integrated with other applications. They are used to perform three main tasks: (1) they alert the Internet user when he watches an inauthentic news video, so that he may discard it, (2) they prevent a Deepfake content from propagating through the network (3) they perform forensic analysis to help track and remove Deepfake content postings.

System for mitigating the problem of deepfake media content using watermarking

The present technology relates to image signal processing. One aspect of the present technology involves analyzing reference imagery (e.g., depicting a conveyor belt) gathered by a camera system to determine which parts of an image frame offer higher probabilities of—relative to other image parts—containing content items. Image blocks representing localized content items can be provided to a signal detector to decode a signal.

Statistical classification systems and methods for distinguishing content items from conveyor belts in automated detection environments

A surface is laser-etched to convey a 2D machine-readable code pattern. Various strategies are detailed to minimize the etching time. Some strategies include modifying the code pattern to reduce a path length traveled by the laser. Some strategies include modifying the code pattern to make it sub-optimal, i.e., making the code pattern a less-faithful approximation of an ideal code pattern. In some embodiments the etched surface is the surface of a plastic container, and the code pattern conveys information indicating the type of plastic of which the container is manufactured. A variety of other features and arrangements are also detailed.

Laser marking of machine-readable codes

The present disclosures relates to decoding machine readable indicia (e.g., a 1D or 2D barcode) in imagery, and related image processing technology. One claim recites a method of locating a barcode within imagery, comprising: converting the imagery to greyscale imagery; evaluating a plurality of blocks within the greyscale imagery, each of the plurality of blocks comprising n×m pixels, where both n and m are positive integers; for each block of the plurality of blocks, determining a value representing pixel diversity within the block; masking the greyscale imagery based on values of the plurality of blocks, in which blocks with a value below a predetermined value of pixel diversity are masked out or excluded; searching the masked, greyscale imagery to determine whether is includes a barcode represented therein. Of course, other claims and combinations are provided too.

Color driven localization of 1D and 2D barcodes in digital capture systems

Methods and arrangements for configuring object localizers

In one aspect, the technology processes image data depicting a physical object to extract payload data that is encoded on the object in the form of tiled code blocks. The payload data is encoded in conjunction with an associated reference signal. To account for possible inversion of the imagery, the decoding includes determining spatial correspondence between the image data and the reference signal. A patch of the image data smaller than the block size is then selected, and correlated with a spatially-corresponding patch of the reference signal. From the correlation it may be concluded that the chosen patch exhibits inversion. In such case a subset of the image data is adjusted prior to decoding to compensate for the inversion. A great number of other features and arrangements are also detailed.

2D code reading in presence of local inversion

An optical code reader classifies a code depicted in input imagery, so that appropriate decoding actions can be invoked. This classification may identify, e.g., (a) whether the code is of a continuous tone or sparse mark variety, (b) which one of different reference signals it includes, and (c) which one of different protocols is used in expressing reference and payload signal components of the code. A great variety of other features and technologies are detailed as well.

Methods and arrangements for optical code classification

Arrangements involving portable devices (e.g., smartphones and tablet computers) are disclosed. One arrangement enables a content creator to select software with which that creator's content should be rendered&#x2014;assuring continuity between artistic intention and delivery. Another utilizes a device camera to identify nearby subjects, and take actions based thereon. Others rely on near field chip (RFID) identification of objects, or on identification of audio streams (e.g., music, voice). Some technologies concern improvements to the user interfaces associated with such devices. Others involve use of these devices in connection with shopping, text entry, sign language interpretation, and vision-based discovery. Still other improvements are architectural in nature, e.g., relating to evidence-based state machines, and blackboard systems. Yet other technologies concern use of linked data in portable devices&#x2014;some of which exploit GPU capabilities. Still other technologies concern computational photography. A great variety of other features and arrangements are also detailed.

Smartphone-based methods and systems

The present invention relates generally to digital watermarking. One aspect of the disclosure includes a method comprising: obtaining data representing imagery; using one or more configured processors, analyzing a plurality of portions of the data to detect a redundantly embedded watermark signal, the analyzing producing detection statistics for each of the plurality of portions, the detection statistics comprising a payload signature, a rotation angle and a scale factor for each portion of the plurality of portions; accumulating payload signatures based on compatible rotation angles and scale factors, said accumulating yielding an accumulated payload signature; and decoding a plural-bit payload from the accumulated payload signature. Of course, many other aspects and disclosure are provided in this patent document.

Hierarchical watermark detector

Spectral encoding methods are more robust when used with improved weak signal detection and synchronizations methods. Further robustness gains are achieved by using informed embedding, error correction and embedding protocols that enable signal to noise enhancements by folding and pre-filtering the received signal.

Robust spectral encoding and decoding methods

The present invention relates generally to digital watermarking. One aspect of the disclosure includes a method comprising: obtaining data representing imagery; using one or more configured processors, analyzing a plurality of portions of the data to detect a watermark orientation component, said analyzing employing a match filter, in which the match filter yields a correlation value for each of the plurality of portions; determining a first portion from the plurality of portions that comprises a correlation value meeting a predetermined value; and directing a watermark decoder at the first portion to decode a plural-bit watermark payload, in which the watermark decoder produces a watermark signature for the first portion, and in which the watermark decoder searches a plurality of areas at or around the first portion to decode the plural-bit watermark payload. Of course, many other aspects and disclosure are provided in this patent document.

Growing community of inventors

Tigard, OR, United States of America

Adnan M Alattar