A steganographic digital watermark signal is decoded from host imagery without requiring a domain transformation for signal synchronization, thereby speeding and simplifying the decoding operation. In time-limited applications, such as in supermarket point-of-sale scanners that attempt watermark decode operations on dozens of video frames every second, the speed improvement allows a greater percentage of each image frame to be analyzed for watermark data. In battery-powered mobile devices, avoidance of repeated domain transformations extends battery life. A great variety of other features and arrangements, including machine learning aspects, are also detailed.

Optical code signal components are generated and then transformed into signal bearing art that conveys machine readable data. The components of an optical code are optimized to achieve improved signal robustness, reliability, capacity and/or visual quality. An optimization program can determine spatial density, dot distance, dot size and signal component priority to optimize robustness. An optical code generator transforms tiles of an optical code or image embedded with the optical code into signal-bearing art using stipple, Voronoi, Delaunay or other graphic drawing methods so as to retain prioritized components of the optical code. The optical code is merged into a host image, such as imagery, text and graphics of a package or label, or it may be printed by itself, e.g., on an otherwise blank label or carton. A great number of other features and arrangements are also detailed.

An example device for processing image data includes a memory configured to store an image; and one or more processors implemented in circuitry and configured to: process the image to identify a pilot signal in the image indicating a portion of the image, the pilot signal forming a boundary around the portion and having pixel values defined according to a mathematical relationship with pixel values within the portion such that the pilot signal is not perceptible to a human user and is detectable the device; determine the portion of the image using the pilot signal; and further process the portion to attempt to detect one or more contents of the portion without attempting to detect the one or more contents of the image in portions of the image outside the portion.

Techniques for providing a virtual touch screen are described. An example of a computing device with a virtual touch screen includes a projector to project a user interface image and a depth camera to detect objects in the vicinity of the user interface image. The computing device also includes a touch service that receives image data from the depth camera and analyzes the image data to generate touch event data. The computing device also includes a User Input (UI) device driver that receives the touch event data from the touch service and reports the touch event data to an operating system of the computing device. The touch service and UI device driver are system level software that is operable prior to a user logging onto the computing device.

Methods and apparatuses for watermark embedding and extracting are provided. A method for watermark embedding includes obtaining a carrier object and watermark information to be embedded in the carrier object; generating at least one encoding region including the watermark information according to the watermark information, the at least one encoding region including a plurality of template lattices; obtaining a watermark image according to the at least one encoding region; and embedding the watermark image in the carrier object.

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.

Provided is an apparatus for preventing a content leak, including: a view request receiving unit for receiving a content view request for view target content to obtain content viewer information; a marker form determining unit for determining a marker form regarding a location of the view target content where a marker for each character is added, according to the content viewer information; a marking method determining unit for determining a marking method regarding a type or order of markers added to the marker form; and a modified content generating unit for generating modified content by adding, to the view target content, one or more markers corresponding to the content viewer information, based on the marker form and the marking method.

An object (e.g., a driver's license) is tested for authenticity using imagery captured by a consumer device (e.g., a mobile phone camera). Corresponding data is sent from the consumer device to a remote system, which has secret knowledge about features indicating object authenticity. The phone, or the remote system, discerns the pose of the object relative to the camera from the captured imagery. The remote system tests the received data for the authentication features, and issues an output signal indicating whether the object is authentic. This testing involves modeling the image data that would be captured by the consumer device from an authentic object—based on the object's discerned pose (and optionally based on information about the camera optics), and then comparing this modeled data with the data sent from the consumer device. A great variety of other features and arrangements are also detailed.

The geometric pose of a patch of watermark data is estimated based on the position of a similar, but non-identical, patch of information within a data structure. The information in the data structure corresponds to a tiled array of calibration patterns that is sampled along at least three non-parallel paths. In a particular embodiment, the calibration patterns are sampled so that edges are globally-curved, yet locally-flat. Use of such information in the data structure enables enhanced pose estimation, e.g., speeding up operation, enabling pose estimation from smaller patches of watermark signals, and/or enabling pose estimation from weaker watermark signals. A great variety of other features and arrangements are also detailed.

An image processing method determines a geometric transform of a suspect image by efficiently evaluating a large number of geometric transform candidates in environments with limited processing resources. Processing resources are conserved by using complementary methods for determining a geometric transform of an embedded signal. One method excels at higher geometric distortion, and specifically, distortion caused by greater tilt angle of a camera. Another method excels at lower geometric distortion, for weaker signals. Together, the methods provide a more reliable detector of an embedded data signal in image across a larger range of distortion while making efficient use of limited processing resources in mobile devices.