جستجوی مقالات مرتبط با کلیدواژه « watermarking » در نشریات گروه « برق »

This paper presents a new watermarking method to improve the robustness and transparency of extracted and host images. The embedding process is based on decomposing of pyramidal directional filter bank and triangular matrix, while the watermark extraction process is based on Mamdani fuzzy logic. In this design, in order to obtain efficient robustness and transparency, the Harris hawks optimization algorithm is used to find the best value of embedding factor. For this purpose, in the embedding algorithm, pyramid directional filter bank decomposition is utilized and accordingly the approximation sub-bands are divided into 8*8 non-overlapping blocks. Moreover, by decomposing the triangular matrix, which embeds the watermark bits in the matrix element, the use of Mamdani implication and the product inference engine have led to an efficient watermark extraction. The simulation results show that the quality of the watermarked image is equal to 60.6dB. Furethermore, applying the proposed algorithm is strong against attacks.

In recent years, illegally copying digital images and even manipulating them, without great loss of quality and at a low cost has been made possible. Watermarking has recently been developed as one of the methods to detect that tampering has occurred and even enable some recovery of the original images. However, there are still many issues to resolve in providing an effective watermark that can detect and recover a wide range of manipulations. Furthermore, the accuracy of detecting and the capability of the recovery of the original images by existing methods are still not at an acceptable level. These problems are more critical when certain high-rate manipulation attacks occur. In this paper, a watermarking method will be introduced that not only is able to detect any tampering, but also can successfully recover the original images in high quality, even at high tampering rates. In this method, Singular Value Decomposition (SVD) is used to detect tampering and Optimal Iterative Block Truncation Coding (OIBTC) has also been applied to recover lost data. This paper proposes a powerful way to increase detection sensitivity while increasing watermark resistance for the effective recovery of corrupted images. The results prove the superiority of the proposed method over current methods.92% of tasks are executed successfully in the edge environment.

Watermerking is a kind of marker covertly embedded in a signal such as audio, video or image data. It is typically used to identify ownership of the copyright of such signal. There are some various ways in watermarking such as using wavelets, Fourier transform or combination of these transforms with matrix decomposition. In this paper, we just use matrix decomposition methods including QR, Hessenberg, Schur, and Singular Value decomposition (SVD). The method consists of two phases. The first one is embedding the watermark image in to the host image. In this stage, we first decompose the matrices corresponding to host and watermark image with one of the known matrix decompositions. Let and be the matrices with highest degree of sparsity in the resulting matrices corresponding to watermark and host images, respectively. Then we compute the matrix , where is a constant factor. Then multiplication of the matrix with the other components of the matrix decomposition corresponding to the host image is considered as the watermarked image which includes a hidden trace of the real owner. After embedding phase, the watermarked image is extracted by an inverse process in the detection phase. We use PSNR and SSIM parameters in order to assess the visual quality and efficiency of the watermarking process. Moreover, the constant should be specified in order to balance between the PSNR corresponding to embedding and detection phases. Numerical experiments are done on some greyscale images in USC-SIPI dataset. Results show that the Hessenberg decomposition has larger PSNR and SSIM values in both embedding and detection phases rather than other matrix decomposition methods. Moreover, watermarked image cannot be extracted in Schur decomposition which in turn shows the weakness of this decomposition. Moreover, numerical experiments reveals improvement and agreement in the PSNR and SSIM parameters, respectively, comparing the most accurate existing methods.

Numerous methods have been introduced for digital images watermarking as well as rubosting them. In this method, with using Graph-based transform and extracts the best graph structure with genetic algorithm so that watermarking can be performed with maximum robustness. One of the common methods in watermarking robustness is the use of discrete cosine transform (DCT). In this study, we have shown that the proposed method is much more powerful than DCT. The proposed method is tested on five different color images such as Lena, Barbara, Boat, Baboon, Peppers. Watermark image (logo) is a random binary image with size 16 x 16 and 8 x 8 pixels. This simulation results show that the proposed method is more robust to similar methods such as discrete cosine transforms. Proposing Watermarking has been evaluated using Bit Error Rate (BER), Structural Similarity Index Measuring (SSIM) and Peak signal-to-noise ratio (PSNR) criteria and different strength Gaussian noise attacks, JPEG compression, median filter, bluring, rescaling, rotate and cropping attacks

In this paper, a new attack is proposed on blind image watermarking, which is able to destroy the watermark embedded in an image using quantization and dither modulation embedding methods. This attack is consist of three main steps: The first two steps are segmentation and finding more similar regions of image and the third step is swapping similar regions with each other. One of the main idea in the proposed method is the algorithm of finding similar segments, which are far from each other and also are in indistinctive locations. This attack does not need to know the embedding and extraction algorithms and their parameters which are used. Therefore, this method is a blind attack. The results of this algorithm and its comparison with other intentional and unintentional attacks show that it can destroy embedded watermark properly and can preserve the quality of watermarked image. The value of NC metric is less than 0.4 and the value of PSNR metric is about 39 dB between the watermarked image and the attacked image.

Today, a large number of multimedia data are easily accessible via the Internet and can be changed or modified simply by using image processing tools. Digital watermarking is a developing technology to ensure and facilitate data validation and security and also protect the copyright of digital media. One of the applications of digital watermarking is authenticating and detecting tampered region. Digital watermarking methods have been proposed for detection, are able to authenticate and check the integrity of the received image by utilizing the information that is already embedded in the media. In this paper, a new method is proposed for the detection of tampered region in the color and grayscale images. In the proposed method, at first, a lifting wavelet transform is applied to the image. Afterward, the horizontal edges are divided into the non-overlapping small blocks and then, the binary watermark is embedded in blocks by quantitating the two maximum factors. To extract the watermark, a set of statistical parameters are calculated for each block and considered as training data for the learning algorithm. For extracting the maximum correlation watermark, the nearest neighbor algorithm is used. Finally, the obtained watermark will be compared with the original watermark and the tampered region will be detected. The experimental results show that the proposed method is capable of detecting tampering area with high accuracy under various attacks such as histogram equalization, Gaussian filter, salt and pepper noise, sharpening, compression, and even combination attacks.

Nowadays, as tampering attacks getting more attention, data protection Radio Frequency Identification tag (RFID) becomes more important. The watermarking approach prevents unauthorized changes on the content of such labels. Due to the limitations of such tags like their simple structure, scarcity of memory bits and its binary content, using conventional methods likes watermarking and hash function are impossible. Thus, the approaches that can be applied to binary data with low size are used. This paper is based on a special algorithm of neural networks that is used to create the hash and the watermarking code that causes fewer number of valuable bits of memory to be consumed. In the proposed algorithm, all watermarking bits are securely protected and locations of the watermark bits is not detectable. This method not only has no need for secrecy watermarking algorithms, but also has other benefits such as ease and speed of implementation. Another advantage of the proposed approach is the two-step algorithm with its keys and using pseudo-random bits location makes watermark's probability of detection very difficult and inaccessible, and also increase the robustness of the method.

Several methods are exploited to watermark digital images as a safety measure for storing information, but an attacker can destroy the information by cropping a segment of the watermarked image or doing salt and pepper noise. In recent years, numerous schemes were proposed that reduce the impact of such attacks. A new method has been proposed to confront cropping attack and salt and pepper noise that is carried out using two Sudoku tables. In this method, the watermark image is scattered in two Sudoku table layouts with different solutions and is watermarked in the host image with Least Significant Bit(LSB). Using this method, the watermark image is repeated 81 times in the host image, and to this effect the watermark image can be reconstructed using other segments when cropped or salt and pepper noise by the attacker. Both Sudokus used in this paper are in the classic 9x9 form and using this method, resistance to cropping attacks increases up to 98.8% and resistance to salt and pepper noise increase up to 80%

Digital watermarking technique embeds additional data (watermark) into digital contents in such a way that the resulting distortion is imperceptible. Tampered detection and recovery is one of the digital watermarking applications. Tamper detection and recovery can mine the tampered region in the image and then recover it. This application can resolve the problem of digital content modification. In this paper, a novel watermarking approach is proposed for tamper detection and recovery in the compressed and uncompressed images. In this method, each block in the image contains watermark of another block. Therefore, for each non-overlapping block in the image, there exists one copy of the watermark. Here, the Chaotic map is used to improve security and confuse block. Also, a secret key is transmitted along with the watermarked image. In our algorithm, a 90% tampered image can be recovered by PSNR ≈ 20 dB. Experimental results demonstrate that the proposed method is secure and superior to the other techniques, especially when the tampered area is large and is resistant to compression.

Watermarking is used to protect copyright proof. Robustness index is the most important parameter that evaluates watermarking algorithm against different attacks such as noise and compression. In this paper، a novel semi- blind image watermarking algorithm based on joint wavelet transform (WT) and singular value decomposition (SVD) transform is proposed. In this algorithm، a new strategy is used to joint WT and SVD effectively. The most important advantage of this algorithm is robustness against a number of common attacks. Experimental results show that the proposed algorithm improves evaluation parameters more than other methods presented previously in the literature.