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.

The present invention provides a method for detecting image steganography based on deep learning, which comprises: filtering images having steganographic class label or true class label in a training set with a high-pass filter to obtain a training set including steganographic class residual images and true class residual images; training a deep network model on said training set to obtain a trained deep model for steganalysis; filtering the image to be detected with said high-pass filter to obtain a residual image to be detected; detecting said residual image to be detected on said deep model so as to determine whether said residual image to be detected is a steganographic image. The method for detecting image steganography in the present invention can create an automatic blind steganalysis model through feature learning and can identify steganographic images accurately.

Systems and methods for applying and detecting cross dependent marks incorporated into an electronic or digital image to form a watermark. The electronic or digital image may include encoded information for example a machine-readable symbol. The watermarking may include an encoding and insertion sub-process that inserts one or more marks into an image at a first point in time for form a marked image, an extraction sub-process that extracts the marks at a second point in time, and a detection sub-process 108 that determines if any modifications have been made to the marked image. The marked image may be formed by determining a first original descriptor and first original mark within the image, determining a second original descriptor and second original mark within the image, and incorporating the first original mark into the second original descriptor and incorporating the second original mark into the first original descriptor.

The present disclosure relate generally to digital watermarking and signal encoding. Various colors can be evaluated and modified to carry an encoded or auxiliary signal.

Multi-blend fingerprinting may be detected. First, a video sample may be received. Next, frames of the received video sample may be step iteratively through until a probability value corresponding to a current frame indicates a match. Deciding that the probability value indicates the match may comprise creating an augmented frame, determining the probability value corresponding to the created augmented frame, and determining that the probability value indicates the match. Then a fingerprint from the created augmented frame may be extracted.

Methods, devices, and computer-program products are provided for adding and decoding data to a digital video signal in a visually imperceptible manner. For example, an encoded video frame can be obtained, and one or more blocks of the encoded video frame can be decoded. Binary data can be added to a subset of pixels from a set of pixels of the one or more blocks. For instance, a pixel component can be modulated to add the binary data. The one or more blocks can be re-encoded using at least one coding mode. The re-encoded one or more blocks can be added to the encoded video frame.

A watermark image may be generated that includes a first set of encoded pixels each of which is assigned a first transparency value and a second set of encoded pixels each of which is assigned a second transparency value, the second transparency level being different from the first transparency level. The encoded pixels may be distributed among a set of blank pixels such that each encoded pixel neighbors one or more blank pixels in the watermark image, and in particular at least two blank pixels in the watermark image. Herein, each blank pixel may be assigned the second transparency value. The watermark image may be overlaid and blended over a background source image to create an encoded source image. A decoder system may recover encoded information from the encoded source image.

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.

A method embeds a watermark image into a host image with adaptive rectangular partition and Lower Upper (LU) decomposition such that a watermarked image is generated with improved computational complexity. The method divides a host image into an Red (R) component, a Green (G) component, and a Blue (B) component, and divides each component of the R, G, and B components into a plurality of MM size blocks, and partitions each of the plurality of MM size blocks into a plurality of non-overlapping blocks with adaptive rectangular partition. The method selects a plurality of embedding blocks from the plurality of MM size blocks for each component of the R, G, and B components of the host image to embed watermark information such that the watermarked image is generated.

A data-bearing image (391) is created from a carrier image (371). The carrier image (371) is scaled to produce a scaled image. A clustered-dot halftone screen is applied to the scaled image to produce a halftone image. A resulting number of cells in the halftone image conforms to a cell count (372) that includes a horizontal cell value and a vertical cell value. Payload data is encoded into the halftone image to produce a data-bearing halftone image, including shifting pixel clusters within cells of the halftone image that include pixel clusters.