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This paper presents a novel robust processing methodology for computing 2.5D thickness maps from dense 3D collocated surfaces. The proposed pipeline is suitable to faithfully adjust data representation detailing as required, from preserving fine surface features to coarse interpretations. The foundations of the proposed technique exploit spatial point-based filtering, ray tracing techniques and the Robust Implicit Moving Least Squares (RIMLS) algorithm applied to dense 3D datasets, such as those acquired from laser scanners. The effectiveness of the proposed technique in overcoming traditional angular aliasing and corruption artifacts is validated with 3D ranging data acquired from internal and external surfaces of exhumed water pipes. It is shown that the resulting 2.5D maps can be more accurately and completely computed to higher resolutions, while significantly reducing the number of raytracing errors when compared with 2.5D thickness maps derived from our current approach.

This paper describes a robotic solution to the structural health inspection of concrete box girders. A combination of sensors including a laser range finder, a depth (RGB-D) camera, an inertial measurement unit and a high-resolution camera are mounted on a tracked robot. The robot can be driven inside a box girder even when there are steps present, to collect high-resolution images of the concrete structure. Software that allows the information captured to be registered with a 3D geometric map of the inside of a box girder, and a visualization tool that can be used to evaluate location-annotated highly-detailed surface condition pictures by the human operator has been developed. The proposed remote evaluation technique makes it feasible to safely monitor areas over a sequence of inspections, leading to more effective maintenance procedures. The effectiveness of the system is illustrated using data gathered during a field trial where the robot was deployed within the Overpass at Huntleyâs Point, in the junction between Victoria Road and Burns Bay Road in Sydney. Functionality to automatically identify defects/regions of interest is also being investigated. It is anticipated that supplementing manual inspection tasks with robotic aids will mitigate the risk to manual entry into a confined space with a consequential saving in associated cost. This project is collaboration between the University of Technology Sydney (UTS) and the Roads & Traffic Authority (RTA) of NSW.

This contribution is about the design of an image compression scheme for near loss-less image compression of a restricted class of images and a specific application. The images are digital diagnostic X-ray images of the coronary vessels of the human heart. This paper proposes a novel compression scheme with a compression ratio of 8 - 10 with preservation of the diagnostic image quality. Central in our approach is the amount of information a trained and highly skilled observer i.e. the cardiologist is able discern at a given exposure and thus quantum noise level. The physics of the image detection process together with the a priori knowledge of the imaging system are the basis of the image statistics. Relevant elements of the human visual system complete the stochastic characterization of imaging process whereon the compression scheme is based.

This article 'Repetitive Sequence-Based Polymerase Chain Reaction of Xanthomonas oryzae pv. oryzae and Pseudomonas species' appeared in the International Rice Research Notes series, created by the International Rice Research Institute (IRRI) to expedite communication among scientists concerned with the development of improved technology for rice and rice-based systems. The series is a mechanism to help scientists keep each other informed of current rice research findings. The concise scientific notes are meant to encourage rice scientists to communicate with one another to obtain details on the research reported.