The WASP Project and SuperWASP Camera

The WASP project and infrastructure supporting the SuperWASP Facility are described. As the instrument, reduction pipeline and archive system are now fully operative we expect the system to have a major impact in the discovery of bright exo-planet candidates as well in more general variable star projects.

Updated parameters for the transiting exoplanet WASP-3b using RISE, a new fast camera for the Liverpool Telescope

Some of the first results are reported from RISE - a new fast camera mounted on the Liverpool Telescope primarily designed to obtain high time-resolution light curves of transiting extrasolar planets for the purpose of transit timing. A full and partial transit of WASP-3 are presented, and a Markov-Chain Monte Carlo analysis is used to update the parameters from the discovery paper. This results in a planetary radius of 1.29(-0.12)(+0.05) R-J and therefore a density of 0.82(-0.09)(+0.14) rho(J), consistent with previous results. The inclination is 85.06(-0.15)(+0.16) deg, in agreement (but with a significant improvement in the precision) with the previously determined value. Central transit times are found to be consistent with the ephemeris given in the discovery paper; however, a new ephemeris calculated using the longer baseline results in T-c(0) = 2 454 605.55915 +/- 0.00023 HJD and P = 1.846835 +/- 0.000002 days.

Robust Extraction of Text from Camera Images using Colour and Spatial Information Simultaneously

The importance and use of text extraction from camera based coloured scene images is rapidly increasing with time. Text within a camera grabbed image can contain a huge amount of meta data about that scene. Such meta data can be useful for identification, indexing and retrieval purposes. While the segmentation and recognition of text from document images is quite successful, detection of coloured scene text is a new challenge for all camera based images. Common problems for text extraction from camera based images are the lack of prior knowledge of any kind of text features such as colour, font, size and orientation as well as the location of the probable text regions. In this paper, we document the development of a fully automatic and extremely robust text segmentation technique that can be used for any type of camera grabbed frame be it single image or video. A new algorithm is proposed which can overcome the current problems of text segmentation. The algorithm exploits text appearance in terms of colour and spatial distribution. When the new text extraction technique was tested on a variety of camera based images it was found to out perform existing techniques (or something similar). The proposed technique also overcomes any problems that can arise due to an unconstraint complex background. The novelty in the works arises from the fact that this is the first time that colour and spatial information are used simultaneously for the purpose of text extraction.

ROSA: A High-cadence, Synchronized Multi-camera Solar Imaging System

The Rapid Oscillations in the Solar Atmosphere (ROSA) instrument is a synchronized, six-camera high-cadence solar imaging instrument developed by Queen's University Belfast. The system is available on the Dunn Solar Telescope at the National Solar Observatory in Sunspot, New Mexico, USA, as a common-user instrument. Consisting of six 1k x 1k Peltier-cooled frame-transfer CCD cameras with very low noise (0.02 -aEuro parts per thousand 15 e s(-1) pixel(-1)), each ROSA camera is capable of full-chip readout speeds in excess of 30 Hz, or 200 Hz when the CCD is windowed. Combining multiple cameras and fast readout rates, ROSA will accumulate approximately 12 TB of data per 8 hours observing. Following successful commissioning during August 2008, ROSA will allow for multi-wavelength studies of the solar atmosphere at a high temporal resolution.

How to estimate scavenger fish abundance using baited camera data

Baited cameras are often used for abundance estimation wherever alternative techniques are precluded, e.g. in abyssal systems and areas such as reefs. This method has thus far used models of the arrival process that are deterministic and, therefore, permit no estimate of precision.
Furthermore, errors due to multiple counting of fish and missing those not seen by the camera have restricted the technique to using only the time of first arrival, leaving a lot of data redundant. Here, we reformulate the arrival process using a stochastic model, which allows the precision of abundance
estimates to be quantified. Assuming a non-gregarious, cross-current-scavenging fish, we show that prediction of abundance from first arrival time is extremely uncertain. Using example data, we show
that simple regression-based prediction from the initial (rising) slope of numbers at the bait gives good precision, accepting certain assumptions. The most precise abundance estimates were obtained
by including the declining phase of the time series, using a simple model of departures, and taking account of scavengers beyond the camera’s view, using a hidden Markov model.