Pawel Korus

Efficient Method for Content Reconstruction With Self-Embedding

This paper presents a new model of the content reconstruction problem in self-embedding systems, based on an erasure communication channel. We explain why such a model is a good fit for this problem, and how it can be practically implemented with the use of digital fountain codes. The proposed method is based on an alternative approach to spreading the reference information over the whole image, which has recently been shown to be of critical importance in the application at hand. Our paper presents a theoretical analysis of the inherent restoration trade-offs. We analytically derive formulas for the reconstruction success bounds, and validate them experimentally with Monte Carlo simulations and a reference image authentication system. We perform an exhaustive reconstruction quality assessment, where the presented reference scheme is compared to five state-of-the-art alternatives in a common evaluation scenario. Our paper leads to important insights on how self-embedding schemes should be constructed to achieve optimal performance. The reference authentication system designed according to the presented principles allows for high-quality reconstruction, regardless of the amount of the tampered content. The average reconstruction quality, measured on 10000 natural images is 37 dB, and is achievable even when 50% of the image area becomes tampered.

Multi-Scale Fusion for Improved Localization of Malicious Tampering in Digital Images

A sliding window-based analysis is a prevailing mechanism for tampering localization in passive image authentication. It uses existing forensic detectors, originally designed for a full-frame analysis, to obtain the detection scores for individual image regions. One of the main problems with a window-based analysis is its impractically low localization resolution stemming from the need to use relatively large analysis windows. While decreasing the window size can improve the localization resolution, the classification results tend to become unreliable due to insufficient statistics about the relevant forensic features. In this paper, we investigate a multi-scale analysis approach that fuses multiple candidate tampering maps, resulting from the analysis with different windows, to obtain a single, more reliable tampering map with better localization resolution. We propose three different techniques for multi-scale fusion, and verify their feasibility against various reference strategies. We consider a popular tampering scenario with mode-based first digit features to distinguish between singly and doubly compressed regions. Our results clearly indicate that the proposed fusion strategies can successfully combine the benefits of small-scale and large-scale analyses and improve the tampering localization performance.

Towards Practical Self-Embedding for JPEG-Compressed Digital Images

This paper deals with the design of a practical self-recovery mechanism for lossy compressed JPEG images. We extend a recently proposed model of the content reconstruction problem based on digital fountain codes to take into account the impact of emerging watermark extraction and block classification errors. In contrast to existing methods, our scheme guarantees a high and stable level of reconstruction quality. Instead of introducing reconstruction artifacts, emerging watermark extraction errors penalize the achievable tampering rates. We introduce new mechanisms that allow for handling high-resolution and color images efficiently. In order to analyze the behavior of our scheme, we derive an improved model to calculate the reconstruction success probability. We introduce a new hybrid mechanism for spreading the reference information over the entire image, which allows to find a good balance between the achievable tampering rates and the computational complexity. Such an approach reduced the watermark embedding time from the order of several minutes to the order of single seconds, even on mobile devices.

Adaptive Self-Embedding Scheme With Controlled Reconstruction Performance

In this paper, we address the problem of adaptive self-embedding, where the reconstruction quality is controlled individually for different fragments of a digital image. We focus on the impact of incorporating content adaptivity features on the restoration success conditions and the achievable reconstruction performance. We analyze the problem theoretically and validate the obtained results experimentally with a fully functional selfembedding scheme. Our analysis shows that introduction of multiple reconstruction profiles, even with significantly lower restoration fidelity, does not need to improve the achievable tampering rate bounds. The obtained fine-grained control over the reconstruction process is exploited to provide guarantees on certain performance aspects. Based on the derived theoretical model, we propose a procedure for optimization of the overall reconstruction quality given constraints on the desired target tampering rate and the required quality level for selected image fragments. Such guarantees are of principal importance in a number of applications.

Multi-Scale Analysis Strategies in PRNU-Based Tampering Localization

Accurate unsupervised tampering localization is one of the most challenging problems in digital image forensics. In this paper, we consider a photo response non-uniformity analysis and focus on the detection of small forgeries. For this purpose, we adopt a recently proposed paradigm of multi-scale analysis and discuss various strategies for its implementation. First, we consider a multi-scale fusion approach, which involves combination of multiple candidate tampering probability maps into a single, more reliable decision map. The candidate maps are obtained with sliding windows of various sizes and thus allow to exploit the benefits of both the small- and large-scale analyses. We extend this approach by introducing modulated threshold drift and content-dependent neighborhood interactions, leading to improved localization performance with superior shape representation and easier detection of small forgeries. We also discuss two novel alternative strategies: a segmentation-guided approach, which contracts the decision statistic to a central segment within each analysis window and an adaptive-window approach, which dynamically chooses analysis window size for each location in the image. We perform extensive experimental evaluation on both synthetic and realistic forgeries and discuss in detail practical aspects of parameter selection. Our evaluation shows that the multi-scale analysis leads to significant performance improvement compared with the commonly used single-scale approach. The proposed multi-scale fusion strategy delivers stable results with consistent improvement in various test scenarios.

A new approach to high-capacity annotation watermarking based on digital fountain codes

Annotation watermarking is a technique that allows to associate content descriptions with digital images in a persistent and format independent manner. It is commonly used in medical applications and, hence, existing schemes have been designed to meet rigorous watermark transparency requirements. As a result, the effective capacity of such schemes is severely limited. In this paper, we present a new approach to annotation watermarking. We adopt the fountain coding paradigm and design a convenient watermark communication architecture which resembles a traditional packet network. Our approach allows for straightforward incorporation of content adaptivity, robustness against cropping and support for multiple data streams. In our study, we focus on high-capacity annotations and we assume different requirements with respect to the fidelity of the watermarked images. Our scheme is robust against lossy JPEG compression and cropping. This paper describes the principles of the proposed approach and presents the results of it’s experimental evaluation.

A scheme for censorship of sensitive image content with high-quality reconstruction ability

Multimedia files often contain fragments with sensitive content that should not be visible to everyone. Such content is usually censored prior to distribution. We propose a technique that allows to blur selected fragments of the image while retaining details necessary for original appearance reconstruction in the image itself. The information is retained by means of a digital watermark. The protected image can be viewed in ordinary viewers and a dedicated decoder is required for content restoration. The decoder ensures that only authorized recipients are able to see the protected fragments. We evaluate the proposed approach in terms of protection capacity and reconstruction quality also under lossy compression. The results show that high image quality is achievable and the proposed scheme might be beneficial for certain applications. Moderate complexity of the decoding process makes it feasible for real-time usage scenarios.

A novel approach to adaptive image authentication

In this paper we address the issue of the trade-off between the tampering rate and the reconstruction quality of image authentication systems. We adopt the fountain coding paradigm and design an adaptive content reconstruction scheme. The scheme conforms the reconstruction quality of individual image fragments both to the local texture properties and to the specified requirements. Experimental evaluation confirms that a framework based on this approach is a valid and convenient model of the performance of the considered reconstruction problem.

Experimental Evaluation of PCE-Based Batch Provisioning of Grid Service Interconnections

If dynamic bandwidth-guaranteed connections between distributed services (e.g., grid services) are provisioned through a centralized system, the policy to serve connection requests might heavily impact both the success in and the time required for setting up user services (e.g., grid-enabled applications). In this paper, the implementation of a batch queue in the centralized system is proposed. By implementing different service policies for the queued requests, connections and, in consequence, user services can be set up with different guarantees. In this study, a bulk-service policy is proposed and implemented to maximize connection set up success. The experimental evaluation results show that the utilization of the proposed policy brings advantages in terms of percentage of accepted connection requests as the number of requests served in one batch increases. Moreover, the achieved improvement does not impact the time required to set up the connections because of the specific LSP set up procedures implemented in the utilized commercial routers.

Digital image integrity – a survey of protection and verification techniques

Abstract We are currently on a verge of a revolution in digital photography. Developments in computational imaging and adoption of artificial intelligence have spawned new editing techniques that give impressive results in astonishingly short time-frames. The advent of multi-sensor and multi-lens cameras will further challenge many existing integrity verification techniques. As a result, it will be necessary to re-evaluate our notion of image authenticity and look for new techniques that could work efficiently in this new reality. The goal of this paper is to thoroughly review existing techniques for protection and verification of digital image integrity. In contrast to other recent surveys, the discussion covers the most important developments both in active protection and in passive forensic analysis techniques. Existing approaches are analyzed with respect to their capabilities, fundamental limitations, and prospective attack vectors. Whenever possible, the discussion is supplemented with real operation examples and a list of available implementations. Finally, the paper reviews resources available in the research community, including public data-sets and commercial or open-source software. The paper concludes by discussing relevant developments in computational imaging and highlighting future challenges and open research problems.