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.

Method and apparatus are disclosed for publishing locational copyrighted watermarking video. According to some embodiments, a method for embedding location information into a video comprises: separating the video into at least one key frame and at least one in-between frame set corresponding to the at least one key frame; receiving location data for the at least one key frame; encrypting the location data for the at least one key frame based on a location private key; and embedding the encrypted location data into the at least one key frame.

Watermark data is converted to watermark coefficients, which may be embedded in an image by converting the image to a frequency domain, embedding the watermark in image coefficients corresponding to medium-frequency components, and converting the modified coefficients to the spatial domain. The watermark data is extracted from the modified image by converting the modified image to a frequency domain, extracting the watermark coefficients from the image coefficients, and determining the watermark data from the watermark coefficients. The watermark data may be truncated image data bits such as truncated least significant data bits. After extraction from the watermark, the truncated image data bits may be combined with data bits representing the original image to increase the bit depth of the image. Watermark data may include audio data portions corresponding to a video frame, reference frames temporally proximate to a video frame, high-frequency content, sensor calibration information, or other image data.

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.

This application discloses a secure face image transmission method performed by an electronic device. In this application, when a camera component of the electronic device acquires any face image, face image information can be read from a buffer. The face image information is used for indicating a quantity of all face images historically acquired by the camera component. Identification information is embedded in the face image to obtain the face image carrying the identification information. The identification information is used for indicating the face image information but not perceivable by a human being. The face image carrying the identification information is transmitted to a remote server for authenticating the face image using the identification information. Therefore, the security of the face image acquired by the camera component is improved, and the security of the face image transmission process is effectively ensured.

The present technology relates to image signal processing. One aspect of the present technology involves analyzing reference imagery gathered by a camera system to determine which parts of an image frame offer high probabilities ofrelative to other image partscontaining decodable signal data. Another aspect of the present technology whittles-down such determined image frame parts based on detected content (e.g., a cereal box) vs expected background within such determined image frame parts.

The present disclosure relate generally to image signal processing, color science and signal encoding. Digital watermarking can be applied to color image data through use of a luminance contrast sensitivity function and a chrominance contrast sensitive function. Of course, other features, combinations and claims are disclosed as well.

The present disclosure relate generally to image signal processing, color science and signal encoding. Digital watermarking can be applied to color image data through use of a luminance contrast sensitivity function and a chrominance contrast sensitive function. Of course, other features, combinations and claims are disclosed as well.

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.

This application discloses a method for processing a face image performed by an electronic device. In this application, when a camera component acquires a face image of a human being in response to a trigger operation, identification information can be read from a memory of the electronic device. The identification information uniquely corresponds to a quantity of all face images acquired by the camera component during a predefined time period. The identification information is embedded into the face image to obtain the face image carrying the identification information. The face image carrying the identification information is transmitted to a remote server for authenticating the human being using the identification information. Therefore, the security of the face image acquired by the camera component is improved, and the security of the face image transmission process is effectively ensured.