We have developed a digital watermarking method that use neural networks to learn embedding and extraction processes that are robust against rotation and JPEG compression. The proposed neural networks consist of a stego-image generator, a watermark extractor, a stego-image discriminator, and an attack simulator. The attack simulator consists of a rotation layer and an additive noise layer, which simulate the rotation attack and the JPEG compression attack, respectively. The stego-image generator can learn embedding that is robust against these attacks, and also, the watermark extractor can extract watermarks without rotation synchronization. The quality of the stego-images can be improved by using the stego-image discriminator, which is a type of adversarial network. We evaluated the robustness of the watermarks and image quality and found that, using the proposed method, high-quality stego-images could be generated and the neural networks could be trained to embed and extract watermarks that are robust against rotation and JPEG compression attacks. We also showed that the robustness and image quality can be adjusted by changing the noise strength in the noise layer.

We propose a method of spread spectrum digital watermarking with quantization index modulation (QIM) and evaluate the method on the basis of IHC evaluation criteria. The spread spectrum technique can make watermarks robust by using spread codes. Since watermarks can have redundancy, messages can be decoded from a degraded stego-image. Under IHC evaluation criteria, it is necessary to decode the messages without the original image. To do so, we propose a method in which watermarks are generated by using the spread spectrum technique and are embedded by QIM. QIM is an embedding method that can decode without an original image. The IHC evaluation criteria include JPEG compression and cropping as attacks. JPEG compression is lossy compression. Therefore, errors occur in watermarks. Since watermarks in stego-images are out of synchronization due to cropping, the position of embedded watermarks may be unclear. Detecting this position is needed while decoding. Therefore, both error correction and synchronization are required for digital watermarking methods. As countermeasures against cropping, the original image is divided into segments to embed watermarks. Moreover, each segment is divided into 8×8 pixel blocks. A watermark is embedded into a DCT coefficient in a block by QIM. To synchronize in decoding, the proposed method uses the correlation between watermarks and spread codes. After synchronization, watermarks are extracted by QIM, and then, messages are estimated from the watermarks. The proposed method was evaluated on the basis of the IHC evaluation criteria. The PSNR had to be higher than 30 dB. Ten 1920×1080 rectangular regions were cropped from each stego-image, and 200-bit messages were decoded from these regions. Their BERs were calculated to assess the tolerance. As a result, the BERs were less than 1.0%, and the average PSNR was 46.70 dB. Therefore, our method achieved a high image quality when using the IHC evaluation criteria. In addition, the proposed method was also evaluated by using StirMark 4.0. As a result, we found that our method has robustness for not only JPEG compression and cropping but also additional noise and Gaussian filtering. Moreover, the method has an advantage in that detection time is small since the synchronization is processed in 8×8 pixel blocks.

This paper proposes a new steganographic method utilizing features of JPEG compression. The method embeds secret information using the number of zeroes in a block of quantized DCT coefficients in minimum coding units (MCU) of JPEG images. In the method, we can embed secret information into JPEG images with degradation like that by JPEG compression. Furthermore, the method causes little change of the histogram of quantized DCT coefficients, so it is hard to perceive secret information embedded by the method. The method mainly modifies boundaries between zero and non-zero DCT coefficients, so we can use the low frequency side of DCT coefficients for another steganographic method.

Digital watermarking systems are required to embed as much information as possible in a digital media without the perceptual distortion as well as to extract it correctly with high probabilities, even though the media is subjected to many kinds of operations. To this end, guided scrambling (GS) techniques, usually used for a recording channel, are applied to digital watermarking systems. A simple GS scheme can make the power of a watermark signal larger against the power of media noise under the condition of preserving the perceptual fidelity, resulting in smaller error probabilities of the retrieved watermark bits. In addition, watermarking systems based on the GS can have more robustness to some specified operations if the prior information on the operations is given to the embedder. JPEG compression is a good example of such an operation when still images are transmitted over the Internet. In order for watermark signals to be more tolerable to the known JPEG attack, the GS-based watermark embedder is informed of advance knowledge of the JPEG compression. Further, a configuration of the GS concatenated with turbo coding is introduced to lower the bit error rate more.

This letter proposes a method which can embed index data such as memos into JPEG images. The method embeds digital watermarks using the quantitative relation between quantized DCT coefficients in JPEG images. In the method, we can embed extra data to represent index data and can extract the index data without parameters used in embedding process. Furthermore, the method is tolerant of JPEG recompression and prevents the degradation of image quality by rewriting index data.