Methods and systems for tracking image senders using client devices are described herein. A computing system may receive an image containing a first watermark vector corresponding to a user account of an image sender. The computing system may convert the image to a frequency domain image that contains the first watermark vector. From the frequency domain image, the computing system may identify the first watermark vector. The computing system may compare the first watermark vector to each of a plurality of stored watermark vectors, each corresponding to a known user account, to determine a probability of a match. The computing system may determine the user account of the sender of the image by determining which of the plurality of stored watermark vectors has a highest probability of a match, and may send, to a workplace administrator platform, an indication of the user account.

The present invention relate generally to signal encoding and decoding. One claim recites a method comprising: obtaining color image data or color video data, the color image data or color video data comprising an encoded signal pattern, the encoded signal pattern aiding detection of an encoded message, the pattern comprising first frequency components and second frequency components, the color image data or color video data comprising first color data and second color data, in which the first color data comprises the first frequency components encoded therein, and the second color data comprises the second frequency components encoded therein; combining the first color data and the second color data, said combining yielding combined color data; utilizing one or more processors or electronic processing circuitry, detecting the encoded signal pattern from the combined color data, said detecting yielding rotation and scale information; and using the rotation and scale information to detect the encoded message from the combined color data. Of course, other combinations and claims are provided too.

Various embodiments are generally directed to utilizing a steganographically encoded image with an offline and/or online verification or authentication protocol. A method for using the steganographic image can include: receiving or utilizing a steganographic image associated with a user at a third-party device, the steganographically encoded image including an identification of a user steganographically encoded with a fingerprint template of the user, and authenticating the user using the steganographically encoded image.

Systems and methods are directed to a computing system. The computing system can include one or more processors, a message embedding model, a message extraction model, and a first set of instructions that cause the computing system to perform operations including obtaining the three-dimensional image data and the message vector. The operations can include inputting three-dimensional image data and a message vector into the message embedding model to obtain encoded three-dimensional image data. The operations can include using the message extraction model to extract an embedded message from the encoded three-dimensional image data to obtain a reconstructed message vector. The operations can include evaluating a loss function for a difference between the reconstructed message vector and the message vector and modifying values for parameters of at least the message embedding model based on the loss function.

Exemplary systems and methods are disclosed for detecting embedded data in a digital image. The system includes a processing device that extracts one or more features from a digital image and analyzes the one or more extracted features in a plurality of steganography analyzers, each steganography analyzer configured to execute a different steganography algorithm. The processing device generates an output data value at each steganography analyzer, the output data value indicating a probability that the digital image includes steganography according to the steganography algorithm of the steganography analyzer. Each output probability value is fed to an ensemble classifier, the ensemble classifier including a neural network in which the output probability values of the plurality of steganography analyzers are ensembled together to generate an output ensemble data value indicating a probability that the digital image includes any steganography according to the steganography algorithms of the steganography analyzers.

A digital watermark analysis apparatus, comprising an image capturing unit for capturing a printed product where additional information is embedded by superimposing a pattern on an image to acquire a captured image, a calculation unit for calculating a spatial frequency characteristic of each small area in the captured image, a specifying unit for specifying an embedded signal strength and an embedding position of the additional information, a decision unit for deciding, based on the embedding position information and the embedded signal strength information, a position in the captured image of a marker detection area for detecting a marker as a reference position for acquiring the additional information, and an acquisition unit for detecting a marker in the marker detection area and acquiring the additional information in the captured image with reference to the detected marker.

Computer-implemented methods and systems are provided for digitally signing predetermined arrays of digital data. Such a method may provide a secret neural network model trained to classify arrays of digital data in dependence on data content of the arrays. The array of the arrays may be signed by supplying the array to the secret neural network model to obtain an initial classification result; and effecting a modification of data in the array to change the initial classification result to a predetermined, secret classification result, the modification being effected via a backpropagation process in the secret neural network model to progressively modify the array in response to backpropagated errors dependent on a difference between a current classification result for the array and the secret classification result.

A video player for playing a video stream that receives a master playlist identifying at least one variant playlist identifying a video file encoded as a series of video frames that when decoded provide the video stream. The video player based upon a configuration tag in the master play list selectively determining whether the video file is to be processed in a trusted execution environment. The trusted execution environment of the video player selectively includes at least one of (i) hack one, only hack one; (ii) output and link protection; (iii) hardware root of trust; and (iv) forensic watermarking, and decrypts and/or decodes the video stream in such an environment.

Imagery captured by an autonomous robot is analyzed to discern digital watermark patterns. In some embodiments, identical but geometrically-inconsistent digital watermark patterns are discerned in an image frame, to aid in distinguishing multiple depicted instances of a particular item. In other embodiments, actions of the robot are controlled or altered in accordance with image processing performed by the robot on a digital watermark pattern. The technology is particularly described in the context of retail stores in which the watermark patterns are encoded, e.g., on product packaging, shelving, and shelf labels. A great variety of other features and arrangements are also detailed.

A system and method for deconstructing a document is described herein, where the method is an improvement over existing document deconstruction techniques. These improvements increase speed and accuracy by rapidly identifying the vendor in an invoice by splitting the invoice into three regions and performing a perceptual image hashing on each section. Then a hamming distance is used to compare the hash for each section with the hashes of known invoices to identify the vendor who sent the invoice.