PRNU pattern alignment for images and videos based on scene content

This paper proposes a novel approach for registering the PRNU pattern between different camera acquisition modes by relying on the imaged scene content. First, images are aligned by establishing correspondences between local descriptors: The result can then optionally be refined by maximizing the PRNU correlation. Comparative evaluations show that this approach outperforms those based on brute-force and particle swarm optimization in terms of reliability, accuracy and speed. The proposed scene-based approach for PRNU pattern alignment is suitable for video source identification in multimedia forensics application

VISION: a video and image dataset for source identification

Abstract Forensic research community keeps proposing new techniques to analyze digital images and videos. However, the performance of proposed tools are usually tested on data that are far from reality in terms of resolution, source device, and processing history. Remarkably, in the latest years, portable devices became the preferred means to capture images and videos, and contents are commonly shared through social media platforms (SMPs, for example, Facebook, YouTube, etc.). These facts pose new challenges to the forensic community: for example, most modern cameras feature digital stabilization, that is proved to severely hinder the performance of video source identification technologies; moreover, the strong re-compression enforced by SMPs during upload threatens the reliability of multimedia forensic tools. On the other hand, portable devices capture both images and videos with the same sensor, opening new forensic opportunities. The goal of this paper is to propose the VISION dataset as a contribution to the development of multimedia forensics. The VISION dataset is currently composed by 34,427 images and 1914 videos, both in the native format and in their social version (Facebook, YouTube, and WhatsApp are considered), from 35 portable devices of 11 major brands. VISION can be exploited as benchmark for the exhaustive evaluation of several image and video forensic tools

A Modified Fourier-Mellin Approach for Source Device Identification on Stabilized Videos

To decide whether a digital video has been captured by a given device, multimedia forensic tools usually exploit characteristic noise traces left by the camera sensor on the acquired frames. This analysis requires that the noise pattern characterizing the camera and the noise pattern extracted from video frames under analysis are geometrically aligned. However, in many practical scenarios this does not occur, thus a re-alignment or synchronization has to be performed. Current solutions often require time consuming search of the realignment transformation parameters. In this paper, we propose to overcome this limitation by searching scaling and rotation parameters in the frequency domain. The proposed algorithm tested on real videos from a well-known state-of-the-art dataset shows promising results

Restoration of renal TIMP3 levels via genetics and pharmacological approach prevents experimental diabetic nephropathy

Background Diabetic nephropathy (DN), one of the major complications of diabetes, is characterized by albuminuria, glomerulosclerosis, and progressive loss of renal function. Loss of TIMP3, an Extracellular Matrix bound protein affecting both inflammation and fibrosis, is a hallmark of DN in human subjects and mouse models.Methods This study was designed to provide evidences that the modulation of the system involving TIMP3 and its target A Disintegrin And Metalloproteinase 17 (ADAM17), may rescue kidney pathology in diabetic mice. Mice with cell-targeted overexpression of TIMP3 in myeloid cells (MacT3), podocyte-specific ADAM17 knockout mice ( increment PodA17), and DBA/2J mice, were rendered diabetic at 8 weeks of age with a low-dose streptozotocin protocol. DBA/2J mice were administered new peptides based on the human TIMP3 N-terminal domain, specifically conjugated with G3C12, a carrier peptide highly selective and efficient for transport to the kidney. Twelve weeks after Streptozotocin injections, 24-hour albuminuria was determined by ELISA, kidney morphometry was analyzed by periodic acid-shift staining, and Real Time-PCR and western blot analysis were performed on mRNA and protein extracted from kidney cortex.Results Our results showed that both genetic modifications and peptides treatment positively affect renal function and structure in diabetic mice, as indicated by a significant and consistent decline in albuminuria along with reduction in glomerular lesions, as indicated by reduced mesangial expansion and glomerular hypertrophy, decreased deposition of extracellular matrix in the mesangium, diminished protein expression of the NADPH oxidases 4 (NOX4), and the improvement of podocyte structural markers such as WT1, nephrin, and podocin. Moreover, the positive effects were exerted through a mechanism independent from glycemic control.Conclusions In diabetic mice the targeting of TIMP3 system improved kidney structure and function, representing a valid approach to develop new avenues to treat this severe complication of diabetes