Automatic localization of tampered regions of a JPEG image has attracted lots of attention in recent times. It is known that the statistical signatures of single and Double JPEG (DJPEG) compression are distinct, and the presence of both the signatures inside an image is proof of manipulation. Automatic localization of tampered regions is carried out by segregating the singly and doubly compressed regions of an image. However, the robustness of the localization process is questionable as very few attempts are made to highlight their vulnerabilities. Here, we propose an adversarial framework, known as jForge, through which one can create a DJPEG compressed image that only bears the signatures of a single compression, and it renders the localization process ineffective. jForge removes the footprints of JPEG compression using model-based approximation techniques. Arguably, this is the first successful attempt to model the DC coefficients of an image, and it employs polynomial regression of two variables to accomplish the same. Similarly, AC coefficients have been approximated using low degree polynomials. We have mounted jForge on three popular forgery localization schemes, and none of them is effective against it. This raises serious doubt regarding the efficacy of the statistical signature-based paradigm of forgery localization.
相似文献Steganography has been a great interest since long time ago. There are a lot of methods that have been widely used since long past. Recently, there has been a growing interest in the use of sparse representation in signal processing. Sparse representation can efficiently model signals in different applications to facilitate processing. Much of the previous work was focused on image and audio sparse representation for steganography. In this paper, a new steganography scheme based on video sparse representation (VSR) is proposed. To exploit proper dictionary, KSVD algorithm is applied to DCT coefficients of Y component related to video (cover) frames. Both I and Q components of video frames are used for secure message insertion. The aim is to hide secret messages into non-zero coefficients of sparse representation of DCT called, I and Q video frames. Several experiments are performed to evaluate the performance of the proposed algorithm, in case of some metrics such as pick signal to noise ratio (PSNR), the hiding ratio (HR), bit error rate (BER) and similarity (Sim) of secret message, and also runtime. The simulation results show that the proposed method exhibits appropriate invisibility and robustness.
相似文献Steganography is a very useful technique which aims at preventing loss of privacy during the process of data communication, especially over the internet. It can involve different forms of media like image, video (i.e., image sequence), audio etc. We propose a novel steganographic approach in spatial domain using pixel value differencing (PVD) or sample value differencing (SVD) technique and Galois field (GF (28)) operations in order to provide a two layered security for hiding message bits. Our method not only has a very high embedding capacity, but is also capable of withstanding statistical attacks. The proposed method embeds from 2 to 6 bits of the message per pixel in each image component, whereas it can embed a minimum of 6 bits and a maximum of 13 bits of message per sample in audio component at the expense of no perceivable distortion and loss of the cover media quality.
相似文献The Secret Sharing Scheme plays a vital role in cryptography which allows to transmit the secret digital information (image, video, audio, handwriting, etc.,) over a communication channel. This cryptographic technique involves encrypting the secret images into noisy shares and transmitted. The transmitted image shares are reconstructed using simple logical computation. In this paper, we propose a secure (n, n)- Multi-Secret-Sharing (MSS) scheme using image scrambling algorithm which is based on the logistic chaotic sequence generated using the secret key which is retrieved from the geometric pattern named as spirograph which drawn by the users with their private values. Also, decomposition and recombination of image pixels which points to change the position and values of the pixels. The experimental results estimate that the standard metrics NPCR, UACI, Entropy, Coefficient Correlation values proves the rigidness of the implemented algorithm.
相似文献Digital image watermarking has become more popular due to its applications in copyright protection and secret communication. Most of the image watermarking algorithms reported till date involve modification of the host contents for embedding a secret data, leading to a reduced robustness and a limited embedding capacity. In the present work, a novel spatial domain watermarking scheme called Pixel Value Search Algorithm (PVSA) is proposed using a linear search operation to achieve high robustness and a theoretically unlimited embedding capacity. In the proposed scheme, secret data are embedded into a host image by mapping their intensity values into row and column locations. Due to this linear mapping of secret data, the host structural content is not altered. In addition, multiple watermarks can be mapped into a single host image using the PVSA technique. The proposed algorithm is verified using MATLAB® simulations and its performance characteristics are assessed using a standard benchmark tool called strimark. Experimental results illustrate the robustness of the PVSA technique against the attacks of Gaussian blurring, Gaussian noise, salt and pepper noise, Poisson noise, speckle noise, mean and median filtering, histogram equalization, image sharpening, intensity transformation, unsharp filtering, JPEG attack, etc. Subsequently an ASIC implementation of the PVSA algorithm is carried out using Verilog HDL and various modules of the Cadence® EDA tool so as to integrate the chip as a watermark co-processor. The ASIC implementation using a 0.18 μm technology at an operating frequency of 100 MHz consumes a power of 326.34 μW for the complete hardware architecture.
相似文献Recently, with the advent of Convolutional Neural Network (CNN) era, Neural style transfer on images has become a very active research topic and the style of an image can be transferred to another image through a CNN so that the image retains both its own content and another style of image. In this work, we propose an algorithm for audio style transfer that uses the force of CNN to generate a new audio from a style audio. We use Continuous Wavelet Transfer(CWT) to convert the audio into a spectrogram and then use the spectrogram as the representation of the audio image through image style transfer method to obtain a new image, and finally, generate an audio using iterative phase reconstruction with Griffin-Lim. We succeed in transferring audio such as light music but had difficulty in transferring audio that has lyrics and high-level metrics such as emotion or tone. We propose several measures to improve the quality of audio and a lot of experimental results shows that our method is better than other methods in terms of sound quality.
相似文献The task of audio and music generation in the waveform domain has become possible due to recent advances in deep learning. Generative Adversarial Networks (GANs) are a type of generative model that has achieved success in areas such as image, video and audio generation. However, realistic audio generation with GANs is still a challenge, thanks to the specific characteristics inherent to this kind of data. In this paper we propose a GAN model that employs the self-attention mechanism and produces small chunks of music conditioned by instrument. We compare our model to a baseline and run ablation studies in order to demonstrate its superiority. We also suggest some applications of the model, particularly in the area of computer assisted composition.
相似文献In this paper, a production–distribution scheduling problem with non-identical batch machines and multiple vehicles is considered. In the production stage, n jobs are grouped into batches, which are processed on m parallel non-identical batch machines. In the distribution stage, there are multiple vehicles with identical capacities to deliver jobs to customers after the jobs are processed. The objective is to minimize the total weighted tardiness of the jobs. Considering the NP-hardness of the studied problem, an algorithm based on ant colony optimization is presented. A new local optimization strategy called LOC is proposed to improve the local exploitation ability of the algorithm and further search the neighborhood solution to improve the quality of the solution. Moreover, two interval candidate lists are proposed to reduce the search for the feasible solution space and improve the search speed. Furthermore, three objective-oriented heuristics are developed to accelerate the convergence of the algorithm. To verify the performance of the proposed algorithm, extensive experiments are carried out. The experimental results demonstrate that the proposed algorithm can provide better solutions than the state-of-the-art algorithms within a reasonable time.
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