Abstract-A copy-move forgery is created by copying and pasting content within the same image, and potentially postprocessing it. In recent years, the detection of copy-move forgeries has become one of the most actively researched topics in blind image forensics. A considerable number of different algorithms have been proposed focusing on different types of postprocessed copies. In this paper, we aim to answer which copy-move forgery detection algorithms and processing steps (e. g. , matching, filtering, outlier detection, affine transformation estimation) perform best in various postprocessing scenarios. The focus of our analysis is to evaluate the performance of previously proposed feature sets. We achieve this by casting existing algorithms in a common pipeline. In this paper, we examined the 15 most prominent feature sets. We analyzed the detection performance on a per-image basis and on a per-pixel basis. We created a challenging real-world copy-move dataset, and a software framework for systematic image manipulation. Experiments show, that the keypoint-based features SIFT and SURF, as well as the block-based DCT, DWT, KPCA, PCA and ZERNIKE features perform very well. These feature sets exhibit the best robustness against various noise sources and downsampling, while reliably identifying the copied regions.

Highlights d Assembly of native AMPARs occurs in discrete steps defined by ER-resident interactors d ABHD6 nurses GluA monomers; FRRS1l/CPT1c complexes drive multimer-formation of GluAs d FRRS1l is a potent regulator of synapse maturation and synaptic plasticity d FRRS1l knockout phenocopies the severe intellectual disability of human patients

Spatial relationships between Ca channels and release sensors at active zones (AZs) are a major determinant of synaptic fidelity. They are regulated developmentally, but the underlying molecular mechanisms are largely unclear. Here, we show that Munc13-3 regulates the density of Ca2.1 and Ca2.2 channels, alters the localization of Ca2.1, and is required for the development of tight, nanodomain coupling at parallel-fiber AZs. We combined EGTA application and Ca-channel pharmacology in electrophysiological and two-photon Ca imaging experiments with quantitative freeze-fracture immunoelectron microscopy and mathematical modeling. We found that a normally occurring developmental shift from release being dominated by Ca influx through Ca2.1 and Ca2.2 channels with domain overlap and loose coupling (microdomains) to a nanodomain Ca2.1 to sensor coupling is impaired in Munc13-3-deficient synapses. Thus, at AZs lacking Munc13-3, release remained triggered by Ca2.1 and Ca2.2 microdomains, suggesting a critical role of Munc13-3 in the formation of release sites with calcium channel nanodomains.

Volume-of-interest imaging offers the possibility to image small volumes at a fraction of the dose of a full scan. Reconstruction methods that do not involve prior knowledge are able to recover almost artifact free images. Although the images appear correct, they often suffer from the problem that low-frequency information that would be included in a full scan is missing. This can often be observed as a scaling error of the reconstructed object densities. As this error is dependent on the object and the truncation in the respective scan, only algorithms that have the correct information about the extent of the object are able to reconstruct the density values correctly.In this paper, we investigate a method to recover the lost low-frequency information. We assume that the correct scaling can be modeled by a linear transformation of the object densities. In order to determine the correct scaling, we employ an atlas of correctly scaled volumes. From the atlas and the given reconstruction volume, we extract patch-based features that are matched against each other. Doing so, we get correspondences between the atlas images and the reconstruction VOI that allow the estimation of the linear transform.We investigated several scenarios for the method: In closed condition, we assumed that a prior scan of the patient was already available. In the open condition test, we excluded the respective patient's data from the matching process. The original offset between the full view and the truncated data was 133 HU on average in the six data sets. The average noise in the reconstructions was 140 HU. In the closed condition, we were able to estimate this scaling up to 9 HU and in open condition, we still could estimate the offset up to 23 HU.

The interaction among particles is a vital aspect of Particle Swarm Optimization. As such, it has a strong influence on the swarm's success. In this study various approaches regarding the particles' communication behavior and their relationship are examined, as well as possibilities to combine the approaches. A new variant of the popular FIPS algorithm, the so-called Ranked FIPS, is introduced, which resolves specific shortcomings of the traditional FIPS. As all tested PSO variants feature distinct strengths and weaknesses, a new adaptive strategy is proposed which operates on dissimiliarly configured subswarms. The exchange between these subswarms is solely based on particle migration. The combination of the Ranked FIPS and other strategies within the so called Particle Swarm Optimizer with Migration achieves a very good, yet remarkably reliable performance over a wide range of recognized benchmark problems.