16,331 research outputs found
Astrometry with the MCAO instrument MAD - An analysis of single-epoch data obtained in the layer-oriented mode
Context: Current instrument developments at the largest telescopes worldwide
have provisions for Multi-Conjugated Adaptive Optics (MCAO) modules. The large
field of view and more uniform correction provided by these systems is not only
highly beneficial for photometric studies but also for astrometric analysis of,
e.g., large dense clusters and exoplanet detection and characterization. The
Multi-conjugated Adaptive optics Demonstrator (MAD) is the first such
instrument and was temporarily installed and tested at the ESO/VLT in 2007. We
analyzed two globular cluster data sets in terms of achievable astrometric
precision. Data were obtained in the layer-oriented correction mode, one in
full MCAO correction mode with two layers corrected (NGC 6388) and the other
applying ground-layer correction only (47 Tuc). Aims: We aim at analyzing the
first available MCAO imaging data in the layer-oriented mode obtained with the
MAD instrument in terms of astrometric precision and stability. Methods: We
calculated Strehl maps for each frame in both data sets. Distortion corrections
were performed and the astrometric precision was analyzed by calculating mean
stellar positions over all frames and by investigation of the positional
residuals present in each frame after transformation to a
master-coordinate-frame. Results: The mean positional precision for stars
between K = 14-18 mag is ~1.2 mas in the full MCAO correction mode data of the
cluster NGC 6388. The precision measured in the GLAO data (47 Tuc) reaches ~1.0
mas for stars corresponding to 2MASS K magnitudes between 9 and 12. The
observations were such that stars in these magnitude ranges correspond to the
same detector flux range. The jitter movement used to scan a larger field of
view introduced additional distortions in the frames, leading to a degradation
of the achievable precision.Comment: 11 pages, 6 figures, accepted for publication in Astronomy &
Astrophysic
On-barn pig weight estimation based on body measurements by structure-from-motion (SfM)
Information on the body shape of pigs is a key indicator to monitor their performance and health and to control or predict their market weight. Manual measurements are among the most common ways to obtain an indication of animal growth. However, this approach is laborious and difficult, and it may be stressful for both the pigs and the stockman. The present paper proposes the implementation of a Structure from Motion (SfM) photogrammetry approach as a new tool for on-barn animal reconstruction applications. This is possible also to new software tools allowing automatic estimation of camera parameters during the reconstruction process even without a preliminary calibration phase. An analysis on pig body 3D SfM characterization is here proposed, carried out under different conditions in terms of number of camera poses and animal movements. The work takes advantage of the total reconstructed surface as reference index to quantify the quality of the achieved 3D reconstruction, showing how as much as 80% of the total animal area can be characterized
Correction of distortion for optimal image stacking in Wide Field Adaptive Optics: Application to GeMS data
The advent of Wide Field Adaptive Optics (WFAO) systems marks the beginning
of a new era in high spatial resolution imaging. The newly commissioned Gemini
South Multi-Conjugate Adaptive Optics System (GeMS) combined with the infrared
camera Gemini South Adaptive Optics Imager (GSAOI), delivers quasi
diffraction-limited images over a field of 2 arc-minutes across. However,
despite this excellent performance, some variable residues still limit the
quality of the analyses. In particular, distortions severely affect GSAOI and
become a critical issue for high-precision astrometry and photometry. In this
paper, we investigate an optimal way to correct for the distortion following an
inverse problem approach. Formalism as well as applications on GeMS data are
presented.Comment: 10 pages, 6 figure
Pigment Melanin: Pattern for Iris Recognition
Recognition of iris based on Visible Light (VL) imaging is a difficult
problem because of the light reflection from the cornea. Nonetheless, pigment
melanin provides a rich feature source in VL, unavailable in Near-Infrared
(NIR) imaging. This is due to biological spectroscopy of eumelanin, a chemical
not stimulated in NIR. In this case, a plausible solution to observe such
patterns may be provided by an adaptive procedure using a variational technique
on the image histogram. To describe the patterns, a shape analysis method is
used to derive feature-code for each subject. An important question is how much
the melanin patterns, extracted from VL, are independent of iris texture in
NIR. With this question in mind, the present investigation proposes fusion of
features extracted from NIR and VL to boost the recognition performance. We
have collected our own database (UTIRIS) consisting of both NIR and VL images
of 158 eyes of 79 individuals. This investigation demonstrates that the
proposed algorithm is highly sensitive to the patterns of cromophores and
improves the iris recognition rate.Comment: To be Published on Special Issue on Biometrics, IEEE Transaction on
Instruments and Measurements, Volume 59, Issue number 4, April 201
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