A live media streaming architecture with real-time live watermarking wherein watermarks are added at a frame or subframe level. The architecture can use a UDP/WebRTC architecture, without requiring a content delivery network, which is not dependent on transmitting media by segments, thus allowing insertion of the watermark at a frame or subframe level. By inserting watermarks at a frame or subframe level, latency is minimized for media delivery to under 500 milliseconds (ms) and for extraction to about five to fifteen seconds.

In an illustrative embodiment, watermark decoding reliability is increased, for images of watermarked objects captured at close distances, by reducing influence of pixel noise (e.g., shot noise). In the same or different embodiment, watermark decoding reliability is increased, for images of watermarked objects captured from far distances, by reducing image under-sampling. A particular implementation down-samples input imagery twice—a first time by a fixed factor, preparatory to performing an FFT, and a second time by a variable factor, preparatory to submitting the image for decoding, where the variable factor is determined using results from the FFT. A number of other features and arrangements are also detailed.

Signal processing devices and methods estimate a geometric transform of an image signal. 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 an image signal in which the reference signal is encoded. Geometric transform candidates encompass differential scale and shear, which are useful in approximating a perspective transform. 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. 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 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 and measuring correlation. The geometric transform is used as an approximation of the geometric distortion of an image after digital data is encoded in it, and is used to compensate for this distortion to facilitate extracting embedded digital messages from the image. Due to the errors in the approximation, a signal confidence metric is determined and used to weight message symbol estimates extracted from the image.

This disclosure relates to advanced image signal processing technology including encoded signals and digital watermarking. One implementation is directed a printed object comprising: a substrate comprising a first area; a first colored ink or design printed within the first area, the first colored ink or design comprising a spectral reflectivity of less than or equal to 20% at or around 660 nm; a colored ink mixture printed over the first colored ink or design at a first plurality of spatial locations within the first area, the colored ink mixture printed such that the first area comprises a second plurality of spatial locations without the colored ink mixture, the colored ink mixture comprising opaque white ink and a first colorant, wherein the color ink mixture comprises a spectral reflectivity greater than the first colored ink or design at or around 660 nm, and wherein colored ink mixture comprises a spectral reflectivity less than the first colored ink or design in the range of 495 nm-570 nm; in which the first plurality of spatial locations is arranged in a pattern conveying an encoded signal, and in which the first colored ink or design and the colored ink mixture comprise a spectral reflectivity difference at or around 660 nm in a difference range of 8%-30%. Of course, other objects, methods, packages, labels, containers, systems and apparatus are described in this patent document.

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.

Techniques for automatically attaching optical character recognition data to images are provided. The techniques include receiving an image file containing an image and performing optical character recognition on the image to generate text output. The techniques then continue by identifying a particular text item from within the generated text output and determining that the particular text item is a value for particular corresponding key. Then metadata that indicates that the particular text item is a value for the particular key is stored in the image file.

An image synthesis method includes inputting an original image and a watermark image into a synthesis model and obtaining a synthesized image output from the synthesis model. The original image and the watermark image are respectively processed in first and second sub-models of the synthesis model and then combined, and the concatenated result is processed in a third sub-model to generate the synthesized image.

A watermark representing a link to an original video and/or metadata such as haptic metadata associated with the original video is embedded in the original video in such a way that a re-recording to the original video can still preserve the watermark. The watermark can be used to link to the original video or to the metadata related thereto.

A user can wear a device which emits a visual and/or audible output. The output changes over time. A system is capable of predicting the output. Thus, the system can analyze a video and determine, based on observed output of the device, whether the video has been modified. The output can be particularly difficult for humans to modify, detect, understand, or recreate, further impeding attempts to disguise edits to the video.

Example apparatus disclosed herein include a watermark detector to detect watermarks in a media signal. Disclosed example apparatus also include a controller to operate the watermark detector to (1) detect a first watermark in the media signal, and (2) cycle between sleep intervals and active intervals based on a repetition rate of the watermarks in the media signal to perform a detection operation for a second watermark at a second location in the media signal relative to a first location of the first watermark in the media signal. In some examples, the controller is to search a buffer of prior detected watermark symbols to detect a third watermark at a third location prior to the second location in the media signal in response to the second watermark not being detected at the second location in the media signal.