This application relates to an image processing method and apparatus, a storage medium, and a computer device. The method includes: obtaining a frequency domain mark image, the frequency domain mark image being obtained by performing frequency domain transformation on a spatial domain mark image; obtaining a transparency parameter configured corresponding to the frequency domain mark image; obtaining target page data; and performing layer superimposition rendering of the frequency domain mark image and the target page data according to the transparency parameter. The solution provided in this application can effectively protect target page data.

A novel process and system for flexibly adding supplemental digital program content such as, for example, transactional advertising content, games, polls, contests, interactive music videos, and e-commerce content generally and the like, into pre-prepared digital media files, such as an MP3 audio file or the like, for playback by digital playback apparatus, wherein the pre-prepared media file is modified by embedding therein executable code representing such supplemental program content, and enabling the playback apparatus to decode and execute the presentation of the supplemental program material as an addition to the playback of the pre-prepared media file content.

This application relates to an image processing method and apparatus, a storage medium, and a computer device. The method includes: obtaining a frequency domain mark image, the frequency domain mark image being obtained by performing frequency domain transformation on a spatial domain mark image; obtaining a transparency parameter configured corresponding to the frequency domain mark image; obtaining target page data; and performing layer superimposition rendering of the frequency domain mark image and the target page data according to the transparency parameter. The solution provided in this application can effectively protect target page data.

The present disclosure provide technology for encoded signal localization. One claim recites an apparatus comprising: memory for buffering image data, the image data having been captured with a camera and depicting product packaging or a product label; one or more processors programmed for: generating a spatial domain feature set representation of a portion of image data; evaluating the spatial domain feature set with a classifier to predict whether the portion of image data includes a transform domain encoded signal. Of course, other claims, and various combinations and embodiments are disclosed in this patent document.

The present disclosures relates generally to image signal processing and encoding signal within imagery.

Systems and methods for display content currentness validation are disclosed. An example method may include accessing, by a validation module executed by a processing device of a computer system, memory associated with a rendering module executed by a graphics processing unit of the computer system to verify that the rendering module renders up to date content on a display device of the computer system, retrieving, from the memory by the validation module, a timestamp embedded in content rendered by the rendering module on the display device, comparing, by the validation module, the timestamp to a current time of the computer system, and responsive to determining that the timestamp does not correspond to the current time of the computer system, determining that the content rendered by the rendering module on the display device is outdated.

Methods, systems and security devices for rendering digital invisible ink, can involve representing an invisible item in a single color that is not discernable from white by a human eye, embedding the invisible item into white space of a digital document, and converting the invisible item into a visible item using a transform table that defines how to convert the single color of the invisible item so that the invisible item after a conversion to the visible item is discernable by the human eye.

Embodiments of the present invention are directed to providing new systems and methods for using deep learning techniques to generate embeddings for high dimensional data objects that can both simulate prior art embedding algorithms and also provide superior performance compared to the prior art methods. Deep learning techniques used by embodiments of the present invention to embed high dimensional data objects may comprise the following steps: (1) generating an initial formal embedding of selected high-dimensional data objects using any of the traditional formal embedding techniques; (2a) designing a deep embedding architecture, which includes choosing the types and numbers of inputs and outputs, types and number of layers, types of units/nonlinearities, and types of pooling, for example, among other design choices, typically in a convolutional neural network; (2b) designing a training strategy; (2c) tuning the parameters of a deep embedding architecture to reproduce, as reliably as possible, the generated embedding for each training sample; (3) optionally deploying the trained deep embedding architecture to convert new high dimensional data objects into approximately the same embedded space as found in step (1); and optionally (4) feeding the computed embeddings of high dimensional objects to an application in a deployed embodiment.

The present disclosures relates generally to image signal processing and encoding signal within imagery. One claim recites a method comprising: obtaining data representing captured imagery, the captured imagery depicting packaging including digital watermarking, the digital watermarking including an orientation signal that is detectable in a transform domain; generating a n-dimensional feature set of the data representing captured imagery, the n-dimensional feature set representing the captured imagery in a spatial domain, where n is an integer great than 13; using a trained classifier to predict the presence of the orientation signal in a transform domain from the feature set in the spatial domain. Of course, other claims and combinations are provided too.

The present disclosures relates generally to image signal processing and encoding signal within imagery. One claim recites a method comprising: obtaining data representing captured imagery, the captured imagery depicting packaging including digital watermarking, the digital watermarking including an orientation signal that is detectable in a transform domain; generating a n-dimensional feature set of the data representing captured imagery, the n-dimensional feature set representing the captured imagery in a spatial domain, where n is an integer great than 13; using a trained classifier to predict the presence of the orientation signal in a transform domain from the feature set in the spatial domain. Of course, other claims and combinations are provided too.