A method and system for hiding reversible data based on prediction errors are provided, where the method includes: partitioning an image, to obtain a shadow part and a blank part; performing a first-layer embedding process on the shadow part; performing a multi-layer embedding process on the blank part; extracting outermost layer information of the blank part after the multilayer embedding process; and extracting information of the shadow part after the first-layer embedding process. According to the method in the present disclosure, a problem of image distortion during high-capacity data embedding can be effectively solved.

A method and system for automatically verifying the authenticity of documents is provided. The method has: scanning a document to be verified in the visible and ultraviolet light spectrum; detecting in the scanned document digital watermarks printed with visible and ultraviolet ink; decrypting the marks, thereby obtaining an ultraviolet mark identifier and a variable data mark identifier; validating the percentage of the mark by checking for the presence of the digital watermark in different areas of the scanned document; comparing the mark identifiers obtained with mark identifiers stored in a database; and determining the validity of the document on the basis of the comparison. The invention allows the validity of the data printed in the document to be checked automatically, reducing the possibility of the undetected falsification, modification or total or partial alteration of a document.

The present disclosure discloses an error modeling method and device for prediction context of reversible image watermarking. A predictor based on omnidirectional context is established; then, the prediction context is self-adaptively error modeled to obtain a self-adaptive error model; and finally, output data from the self-adaptive error model is fed back to the predictor to update and correct the prediction context, so as to correct a prediction value of a current pixel x[i,j]. Since the non-linear correlation between the current pixel and the prediction context thereof, i.e., the non-linear correlation redundancy between pixels can be found by the error modeling of the prediction context of the predictor, the non-linear correlation redundancy between the pixels can be effectively removed. Thus, the embeddable watermarking capacity can be increased.

An image processing apparatus includes processing circuitry. The processing circuitry is configured to compose background information with latent image information to generate a latent-image-embedded image, add the latent-image-embedded image to print data, and at least one of extract the latent image information from the print data and extract the background information from the print data.

A method may include obtaining a first byte stream from first document code and a second byte stream from second document code. The first document code has a document type and the second document code has the document type. The method may further include identifying, in the first byte stream, nonvisual noise corresponding to a custom byte code defined in a custom character encoding set. The nonvisual noise is invisible when rendering the first document code. The method may further include replacing, in the first byte stream, the custom byte code with at least one standard byte code defined in a standard character encoding set to obtain modified document code. The second document code uses the standard character encoding set. The method may further include comparing the modified document code with the second document code by comparing the first byte stream with the second byte stream.

The present disclosure provides a method and system for large-capacity image steganography and recovery based on an invertible neural networks. The method is intended to embed one or more hidden images into a single host image, and recover all the hidden images from a stego image. The method designs an image steganography model that supports bidirectional mapping. The model includes cascaded invertible modules containing a host branch and a hidden branch. A hidden image is embedded into a host image through forward mapping to form a stego image, and the host image and the hidden image are separated and recovered from the single stego image through reverse mapping.

A method and system for automatically verifying the authenticity of documents is provided. The method has: scanning a document to be verified in the visible and ultraviolet light spectrum; detecting in the scanned document digital watermarks printed with visible and ultraviolet ink; decrypting the marks, thereby obtaining an ultraviolet mark identifier and a variable data mark identifier; validating the percentage of the mark by checking for the presence of the digital watermark in different areas of the scanned document; comparing the mark identifiers obtained with mark identifiers stored in a database; and determining the validity of the document on the basis of the comparison. The invention allows the validity of the data printed in the document to be checked automatically, reducing the possibility of the undetected falsification, modification or total or partial alteration of a document.

An image processing apparatus includes processing circuitry. The processing circuitry is configured to compose background information with latent image information to generate a latent-image-embedded image, add the latent-image-embedded image to print data, and at least one of extract the latent image information from the print data and extract the background information from the print data.

The present disclosure discloses an error modeling method and device for prediction context of reversible image watermarking. A predictor based on omnidirectional context is established; then, the prediction context is self-adaptively error modeled to obtain a self-adaptive error model; and finally, output data from the self-adaptive error model is fed back to the predictor to update and correct the prediction context, so as to correct a prediction value of a current pixel x[i,j]. Since the non-linear correlation between the current pixel and the prediction context thereof, i.e., the non-linear correlation redundancy between pixels can be found by the error modeling of the prediction context of the predictor, the non-linear correlation redundancy between the pixels can be effectively removed. Thus, the embeddable watermarking capacity can be increased.

A device includes a processor and associated memory; and a compressor for compressing data representing an electronic document, the electronic document comprising a number of objects. The compressor is to determine for each object of the document whether data of that object is to be compressed with lossy or lossless compression and to compress the data accordingly to generate a compressed electronic document.