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.

An image forensics system estimates a camera response function (CRF) associated with a digital image, and compares the estimated CRF to a set of rules and compares the estimated CRF to a known CRF. The known CRF is associated with a make and a model of an image sensing device. The system applies a fusion analysis to results obtained from comparing the estimated CRF to a set of rules and from comparing the estimated CRF to the known CRF, and assesses the integrity of the digital image as a function of the fusion analysis.

In one example, a method for inserting a digital watermark in a signal includes obtaining the signal comprising a plurality of frames, inserting a first digital watermark in a first frame of the plurality of frames, inserting a second digital watermark in a second frame of the plurality of frames, wherein the second digital watermark differs from the first digital watermark in at least one way selected from a group of: a location within a respective frame, a number of bits, a pattern of bits, and a number of bits of a noise, and outputting a watermarked signal including the first digital watermark in the first frame and the second digital watermark in the second frame.

Methods, apparatus and articles of manufacture (e.g., computer readable media) to detect watermark modifications are disclosed. Example apparatus disclosed herein include means for encoding a first watermark in a first media signal obtained from an output of a media device to obtain a second media signal encoded with the first watermark and a second watermark, the second watermark already encoded in the first media signal obtained from the output of the media device. Disclosed example apparatus also include means for decoding the first watermark and the second watermark from the second media signal to determine a first metric corresponding to the first watermark and a second metric corresponding to the second watermark. Disclosed example apparatus further include means for outputting, based on the first metric and the second metric, an indication of whether the second watermark has been modified.

Systems and methods are provided for decoding watermarks in video frames. A media device may receive a video frame that includes a first predetermined region comprising a watermark and a second predetermined region having pixel values selected to reduce the perceptibility of the first predetermined region. The media device may detect the watermark in the first predetermined region of the video frame and identify one or more contiguous subsets of pixels that correspond to a first pixel value and one or more contiguous subsets of pixels that correspond to a second pixel value. The media device then assigns a first symbol to the one or more contiguous subsets of pixels that correspond to the first pixel value and second symbol the one or more contiguous subsets of pixels that correspond to the second pixel value. The media device then generates a first sequence of symbols from the assigned symbols.

This disclosure relates to counterfeit detection and deterrence using advanced signal processing technology including steganographic embedding and digital watermarking. Digital watermark can be used on consumer products, labels, logos, hang tags, stickers and other objects to provide counterfeit detection mechanisms.

Features from a style image are adapted to express a machine-readable code. For example, grains of rice depicted in a style image may be positioned to create a pattern mimicking that of a machine-readable code. The resulting output image can then be used as a graphical component in product packaging (e.g., as a background, border, or pattern fill), while also serving to convey a product identifier to a compliant reader device (e.g., a retail point-of-sale terminal). In some embodiments, a neural network is trained to apply a particular style image to machine readable codes. A great variety of other features and arrangements are also detailed.

There is provided a method for embedding a digital watermark into and extracting a digital watermark from a numerical data set. In accordance with embodiments of the present disclosure, there is provided a method for embedding a digital watermark into a numerical data set. The method includes selecting portions of the numerical data set identified as data noise, the selected portions to be used for embedding the digital watermark into the numerical data set, the digital watermark being unique for each recipient of the numerical data. The method further includes replacing the least significant bit (LSB) of at least some of the selected portions of the numerical data set with at least portion of the digital watermark.

A method is provided for watermarking a machine learning model used for object detection or image classification. In the method, a first subset of a labeled set of ML training samples is selected. The first subset is of a predetermined class of images. In one embodiment, the first pixel pattern is selected and sized to have substantially the same dimensions as each sample of the first subset or each bounding box in the case of an object detector. Each sample of the first subset is relabeled to have a different label than the original label. An opacity of the pixel pattern may be adjusted independently for different parts of the pattern. The ML model is trained with the labeled set of ML training samples and the first subset of relabeled ML training samples. Using multiple different opacity factors provides both reliability and credibility to the watermark.