On The Extended Knotted Disks of Galaxies

The stellar disks of many spiral galaxies are twice as large as generally thought. We use archival data from the Galaxy Evolution Explorer mission (GALEX) to quantify the statistical properties of young stellar clusters in the outer, extended disks of a sample of eleven nearby galaxies. We find an excess of sources between 1.25 and 2 optical radii, R(25), for five of the galaxies, which statistically implies that at least a quarter of such galaxies have this cluster population (90% confidence level), and no significant statistical excess in the sample as a whole beyond 2 optical radii, even though one galaxy (M 83) individually shows such an excess. Although the excess is typically most pronounced for blue (FUV -NUV < 1, NUV < 25) sources, there is also an excess of sources with redder colors. Although from galaxy to galaxy the number of sources varies significantly, on average, the galaxies with such sources have 75 +- 10 blue sources at radii between 1.25 and 2 R(25). In addition, the radial distribution is consistent with the extended dust emission observed in the far IR and with the properties of H-alpha sources, assuming a constant cluster formation rate over the last few hundred Myrs. All of these results suggest that the phenomenon of low-level star formation well outside the apparent optical edges of disks (R ~ R(25)) is common and long-lasting.Comment: 8 pages, accepted for publication in A

Measuring Outer Disk Warps with Optical Spectroscopy

Warps in the outer gaseous disks of galaxies are a ubiquitous phenomenon, but it is unclear what generates them. One theory is that warps are generated internally through spontaneous bending instabilities. Other theories suggest that they result from the interaction of the outer disk with accreting extragalactic material. In this case, we expect to find cases where the circular velocity of the warp gas is poorly correlated with the rotational velocity of the galaxy disk at the same radius. Optical spectroscopy presents itself as an interesting alternative to 21-cm observations for testing this prediction, because (i) separating the kinematics of the warp from those of the disk requires a spatial resolution that is higher than what is achieved at 21 cm at low HI column density; (ii) optical spectroscopy also provides important information on star formation rates, gas excitation, and chemical abundances, which provide clues to the origin of the gas in warps. We present here preliminary results of a study of the kinematics of gas in the outer-disk warps of seven edge-on galaxies, using multi-hour VLT/FORS2 spectroscopy.Comment: 7 pages, 7 figures; to appear in the proceedings of IAU Symposium 254 "The Galaxy disk in a cosmological context", Copenhagen, June 200

An Evaluation of Popular Copy-Move Forgery Detection Approaches

A copy-move forgery is created by copying and pasting content within the same image, and potentially post-processing 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.Comment: Main paper: 14 pages, supplemental material: 12 pages, main paper appeared in IEEE Transaction on Information Forensics and Securit

Galaxy Luminosity Functions from Deep Spectroscopic Samples of Rich Clusters

Using a new spectroscopic sample and methods accounting for spectroscopic sampling fractions that vary in magnitude and surface brightness, we present R-band galaxy luminosity functions (GLFs) for six nearby galaxy clusters with redshifts 4000 < cz < 20000 km/s and velocity dispersions 700 < sigma < 1250 km/s. In the case of the nearest cluster, Abell 1060, our sample extends to M_R=-14 (7 magnitudes below M*), making this the deepest spectroscopic determination of the cluster GLF to date. Our methods also yield composite GLFs for cluster and field galaxies to M_R=-17 (M*+4), including the GLFs of subsamples of star forming and quiescent galaxies. The composite GLFs are consistent with Schechter functions (M*_R=-21.14^{+0.17}_{-0.17}, alpha=-1.21^{+0.08}_{-0.07} for the clusters, M*_R=-21.15^{+0.16}_{-0.16}, alpha=-1.28^{+0.12}_{-0.11} for the field). All six cluster samples are individually consistent with the composite GLF down to their respective absolute magnitude limits, but the GLF of the quiescent population in clusters is not universal. There are also significant variations in the GLF of quiescent galaxies between the field and clusters that can be described as a steepening of the faint end slope. The overall GLF in clusters is consistent with that of field galaxies, except for the most luminous tip, which is enhanced in clusters versus the field. The star formation properties of giant galaxies are more strongly correlated with the environment than those of fainter galaxies.Comment: 53 pages, 8 figures, 1 ASCII table; accepted for publication in Ap

Unsupervised Feature Learning for Writer Identification and Writer Retrieval

Deep Convolutional Neural Networks (CNN) have shown great success in supervised classification tasks such as character classification or dating. Deep learning methods typically need a lot of annotated training data, which is not available in many scenarios. In these cases, traditional methods are often better than or equivalent to deep learning methods. In this paper, we propose a simple, yet effective, way to learn CNN activation features in an unsupervised manner. Therefore, we train a deep residual network using surrogate classes. The surrogate classes are created by clustering the training dataset, where each cluster index represents one surrogate class. The activations from the penultimate CNN layer serve as features for subsequent classification tasks. We evaluate the feature representations on two publicly available datasets. The focus lies on the ICDAR17 competition dataset on historical document writer identification (Historical-WI). We show that the activation features trained without supervision are superior to descriptors of state-of-the-art writer identification methods. Additionally, we achieve comparable results in the case of handwriting classification using the ICFHR16 competition dataset on historical Latin script types (CLaMM16).Comment: ICDAR2017 camera ready (fixed p@2 values, missing table references

Automatic Dating of Historical Documents

With the growing number of digitized documents available to researchers it is becoming possible to answer scientific questions by simply analyzing the image content. In this article, a new approach for the automatic dating of historical documents is proposed. It is based on an approach only recently proposed for scribe identification. It uses local RootSIFT descriptors which are encoded using VLAD. The method is evaluated using a dataset consisting of context areas of medieval papal charters covering around 150 years from 1049 to 1198 AD. Experimental results show very promising mean absolute errors of about 17 years

Convolution and deconvolution based estimates of galaxy scaling relations from photometric redshift surveys

In addition to the maximum likelihood approach, there are two other methods which are commonly used to reconstruct the true redshift distribution from photometric redshift datasets: one uses a deconvolution method, and the other a convolution. We show how these two techniques are related, and how this relationship can be extended to include the study of galaxy scaling relations in photometric datasets. We then show what additional information photometric redshift algorithms must output so that they too can be used to study galaxy scaling relations, rather than just redshift distributions. We also argue that the convolution based approach may permit a more efficient selection of the objects for which calibration spectra are required.Comment: 7 pages, 4 figures, accepted for publication in MNRAS; v2 includes a new section and other minor change

The IR Luminosity Functions of Rich Clusters

We present MIPS observations of the cluster A3266. About 100 spectroscopic cluster members have been detected at 24 micron. The IR luminosity function in A3266 is very similar to that in the Coma cluster down to the detection limit L_IR~10^43 ergs/s, suggesting a universal form of the bright end IR LF for local rich clusters with M~10^15 M_sun. The shape of the bright end of the A3266-Coma composite IR LF is not significantly different from that of nearby field galaxies, but the fraction of IR-bright galaxies (SFR > 0.2M_sun/yr) in both clusters increases with cluster-centric radius. The decrease of the blue galaxy fraction toward the high density cores only accounts for part of the trend; the fraction of red galaxies with moderate SFRs (0.2 < SFR < 1 M_sun/yr) also decreases with increasing galaxy density. These results suggest that for the IR bright galaxies, nearby rich clusters are distinguished from the field by a lower star-forming galaxy fraction, but not by a change in L*_IR. The composite IR LF of Coma and A3266 shows strong evolution when compared with the composite IR LF of two z~0.8 clusters, MS 1054 and RX J0152, with L*_IR \propto (1+z)^{3.2+/-0.7},Phi*_IR \propto (1+z)^{1.7+/-1.0}. This L*_IR evolution is indistinguishable from that in the field, and the Phi*_IR evolution is stronger, but still consistent with that in the field. The similarity of the evolution of bright-end IR LF in very different cluster and field environments suggests either this evolution is driven by the mechanism that works in both environments, or clusters continually replenish their star-forming galaxies from the field, yielding an evolution in the IR LF that is similar to the field. The mass-normalized integrated star formation rates (SFRs) of clusters within 0.5R_200 also evolve strongly with redshift, as (1+z)^5.3.Comment: 15 pages, 8 figures, 1 table, accepted by Ap

Disentangling Morphology, Star Formation, Stellar Mass, and Environment in Galaxy Evolution

We present a study of the spectroscopic and photometric properties of galaxies in six nearby clusters. We perform a partial correlation analysis on our dataset to investigate whether the correlation between star formation rates in galaxies and their environment is merely another aspect of correlations of morphology, stellar mass, or mean stellar age with environment, or whether star formation rates vary independently of these other correlations. We find a residual correlation of ongoing star formation with environment, indicating that even galaxies with similar morphologies, stellar masses, and mean stellar ages have lower star formation rates in denser environments. Thus, the current star formation gradient in clusters is not just another aspect of the morphology-density, stellar mass-density, or mean stellar age-density relations. Furthermore, the star formation gradient cannot be solely the result of initial conditions, but must partly be due to subsequent evolution through a mechanism (or mechanisms) sensitive to environment. Our results constitute a true ``smoking gun'' pointing to the effect of environment on the later evolution of galaxies.Comment: 31 pages, including 5 figures; accepted for publication in Ap