METHODOLOGY FOR ASSESSING THE EFFECTIVENESS OF METHODS FOR EMBEDDING DIGITAL WATERMARKS

In recent years, we have seen a significant increase in traffic moving across various networks and channels. The development of technology and global network leads to an increase in the amount of multimedia traffic. To authenticate and avoid abuse, data should be protected with watermarks. This paper discusses various robust and invisible watermarking methods in the spatial domain and the transform domain. The basic concepts of digital watermarks, important characteristics and areas of application of watermarks are considered in detail. The paper also presents the most important criteria for assessing the digital watermark effectiveness. Based on the analysis of the current state of the digital watermarking methods, robustness, imperceptibility, security and payload have been determined as the main factors in most scientific works. Moreover, researchers use different methods to improve / balance these factors to create an effective watermarking system. Our research identified the main factors and new techniques used in modern research. And the assessment of watermark method effectiveness was proposed.

Additional Information Delivery to Image Content via Improved Unseen–Visible Watermarking

In a practical watermark scenario, watermarks are used to provide auxiliary information; in this way, an analogous digital approach called unseen–visible watermark has been introduced to deliver auxiliary information. In this algorithm, the embedding stage takes advantage of the visible and invisible watermarking to embed an owner logotype or barcodes as watermarks; in the exhibition stage, the equipped functions of the display devices are used to reveal the watermark to the naked eyes, eliminating any watermark exhibition algorithm. In this paper, a watermark complement strategy for unseen–visible watermarking is proposed to improve the embedding stage, reducing the histogram distortion and the visual degradation of the watermarked image. The presented algorithm exhibits the following contributions: first, the algorithm can be applied to any class of images with large smooth regions of low or high intensity; second, a watermark complement strategy is introduced to reduce the visual degradation and histogram distortion of the watermarked image; and third, an embedding error measurement is proposed. Evaluation results show that the proposed strategy has high performance in comparison with other algorithms, providing a high visual quality of the exhibited watermark and preserving its robustness in terms of readability and imperceptibility against geometric and processing attacks.

Towards High-Resolution Copy-Evident Ceramic Tiles: A Deep Learning Framework for Halftoning and Watermarking

Ceramic art is essential in interior design and decoration, and making exquisite ceramic tiles imposes strict requirements for inkjet printing technology. High-resolution ceramic tiles are often produced through inkjet printing, in which the input images are converted into a halftone format. However, traditional binary halftoning techniques cannot produce high-resolution images for the ensuing printing process. Given that the processes of inkjet printing and high-temperature firing of ceramic tiles are a highly complex nonlinear system, and existing halftoning methods pose intractable problems, including inconsistent textures and color deviations. Based on a modified U-Net model and a modified error diffusion algorithm, we propose a multilevel halftoning method, which is capable of converting color-separation images of ceramic tiles into high-resolution halftone images. To deter copyright infringement, we further apply an ad hoc invisible watermarking method for halftone images. In this paper, we propose a four-stage framework: (1) A self-built dataset is used to solve non-convergence and overfitting problems caused by the unbalanced samples and non-uniqueness of halftone images. (2) A modified U-Net model is trained on the self-built dataset and applied to the ceramic-tile images. (3) An improved error diffusion algorithm is used to calibrate and convert the predicted continuous-tone transition images into multilevel halftone images for inkjet printing. (4) A invisible and robust watermark is embedding algorithm towards halftone images is proposed for copyright protection. Experimental results show that our methodology is effective for performing the color-to-halftone transformation and identifying the copyright.

A Hidden DCT-Based Invisible Watermarking Method for Low-Cost Hardware Implementations

This paper presents an invisible and robust watermarking method and its hardware implementation. The proposed architecture is based on the discrete cosine transform (DCT) algorithm. Novel techniques are applied as well to reduce the computational cost of DCT and color space conversion to achieve low-cost and high-speed performance. Besides, a watermark embedder and a blind extractor are implemented in the same circuit using a resource-sharing method. Our approach is compatible with various watermarking embedding ratios, such as 1/16 and 1/64, with a PSNR of over 45 and the NC value of 1. After Joint Photographic Experts Group (JPEG) compression with a quality factor (QF) of 50, our method can achieve an NC value of 0.99. Results from a design compiler (DC) with TSMC-90 nm CMOS technology show that our design can achieve the frequency of 2.32 GHz with the area consumption of 304,980.08 μm2 and power consumption of 508.1835 mW. For the FPGA implementation, our method achieved a frequency of 421.94 MHz. Compared with the state-of-the-art works, our design improved the frequency by 4.26 times, saved 90.2% on area and increased the power efficiency by more than 1000 fold.

Optimasi Hybrid Invisible Watermarking RDWT-DCT-SVD menggunakan Algoritma PSO pada Citra Digital

Begitu mudahnya di era digital ini dalam menduplikasi dan mendistribusi berbagai macam informasi khususnya pada data citra yang membuat sebagian orang menggunakan untuk keperluan yang negatif karena dengan melakukan penyimpangan informasi citra tentu melanggar hak cipta intelektual dari kepemilikan data. Metode watermarking merupakan salah satu pendekatan untuk perlindungan hak cipta. Dalam penerapan watermark ada beberapa cara, salah satunya adalah hybrid invisible watermark. Penelitian oleh Anu Bajaj pada tahun 2013 yang menggabungan teknik RDWT-DCT-SVD dengan membuktikan hasil efisiensinya dengan nilai PSNR terhadap serangan yang berbeda. Namun pada saran penelitian tersebut menyebutkan bahwa kombinasi hybrid watermarking tidak aman, sehingga pada penelitian selanjutnya disarankan harus menambahkan keamanan berupa optimasi dari segi penyisipan informasi ke dalam citra masukannya, agar dapat meningkatkan skema penilaian PSNR yang aman dan lebih tinggi. Tujuan dari penelitian ini adalah penulis menambahkan algoritma PSO untuk dikombinasi dengan metode hybrid tersebut dengan tujuan dapat menghasilkan keamanan dari segi penyisipan dan menghasilkan peningkatan dari skema PSNR. Berdasarkan hasil analisis, pengujian dan komparasi dapat disimpulkan bahwa hybrid invisible watermarking RDWT-DCT-SVD dengan optimasi PSO memiliki hasil yang signifikan lebih tinggi dengan rata-rata 50 dB sehingga memiliki kualitas imperceptibility yang lebih baik.

A Grid-based Invisible Watermarking for .Jpeg Images Using Least Significant Bit

Internet is a one stop centre for users to download any media file such as image, audio and even videos. It is an excellent distribution system for digital media as it is inexpensive, eliminates warehousing and stock and user-friendly. However, there is an issue where user may copy or share the data illegally which eventually can increase the risk of privacy level of the media. Digital watermarking is introduced in order to solve the issue where it can provide copyright protection of the media and also to provide ownership that can be used to protect data from piracy. An efficient scheme of invisible watermarking is that it has to be able to overcome attacks on social media such in a way where when people download and crop any image from social media, the owner of the image can proof that the image is rightfully his. The loss of synchronization caused by geometrical modifications of an image, such as cropping, increases the difficulty of watermark detection, especially for invisible watermarking schemes. In this research, the Spatial Domain technique based algorithms were considered and two experiments were conducted in where one is text-based watermark embedding and another is image-based watermark embedding, The text-based watermarking method preserved the watermark after being uploaded and download to social media but decreases in terms of size of image. For the case of image-based watermark, the watermark was preserved for images with minimal colours or solid colours. It has also survived the watermark originality once being uploaded to social media.

Model Watermarking for Image Processing Networks

Deep learning has achieved tremendous success in numerous industrial applications. As training a good model often needs massive high-quality data and computation resources, the learned models often have significant business values. However, these valuable deep models are exposed to a huge risk of infringements. For example, if the attacker has the full information of one target model including the network structure and weights, the model can be easily finetuned on new datasets. Even if the attacker can only access the output of the target model, he/she can still train another similar surrogate model by generating a large scale of input-output training pairs. How to protect the intellectual property of deep models is a very important but seriously under-researched problem. There are a few recent attempts at classification network protection only.In this paper, we propose the first model watermarking framework for protecting image processing models. To achieve this goal, we leverage the spatial invisible watermarking mechanism. Specifically, given a black-box target model, a unified and invisible watermark is hidden into its outputs, which can be regarded as a special task-agnostic barrier. In this way, when the attacker trains one surrogate model by using the input-output pairs of the target model, the hidden watermark will be learned and extracted afterward. To enable watermarks from binary bits to high-resolution images, both traditional and deep spatial invisible watermarking mechanism are considered. Experiments demonstrate the robustness of the proposed watermarking mechanism, which can resist surrogate models learned with different network structures and objective functions. Besides deep models, the proposed method is also easy to be extended to protect data and traditional image processing algorithms.