Sample-induced beam distortions in terahertz time domain spectroscopy and imaging systems

It is demonstrated that distortion of the terahertz beam profile and generation of a cross-polarised component occur when the beam in terahertz time domain spectroscopy and imaging systems interacts with the sample under test. These distortions modify the detected signal, leading to spectral and image artefacts. The degree of distortion depends on the optical design of the system as well as the properties of the sample.

A bridge-ship collision avoidance system based on FLIR image sequences

In this paper, a forward-looking infrared (FLIR) video surveillance system is presented for collision avoidance of moving ships to bridge piers. An image preprocessing algorithm is proposed to reduce clutter background by multi-scale fractal analysis, in which the blanket method is used for fractal feature computation. Then, the moving ship detection algorithm is developed from image differentials of the fractal feature in the region of surveillance between regularly interval frames. When the moving ships are detected in region of surveillance, the device for safety alert is triggered. Experimental results have shown that the approach is feasible and effective. It has achieved real-time and reliable alert to avoid collisions of moving ships to bridge piers.

Integrating features for man-made target tracking from FLIR image sequence using particle filter

A new man-made target tracking algorithm integrating features from (Forward Looking InfraRed) image sequence is presented based on particle filter. Firstly, a multiscale fractal feature is used to enhance targets in FLIR images. Secondly, the gray space feature is defined by Bhattacharyya distance between intensity histograms of the reference target and a sample target from MFF (Multi-scale Fractal Feature) image. Thirdly, the motion feature is obtained by differencing between two MFF images. Fourthly, a fusion coefficient can be automatically obtained by online feature selection method for features integrating based on fuzzy logic. Finally, a particle filtering framework is developed to fulfill the target tracking. Experimental results have shown that the proposed algorithm can accurately track weak or small man-made target in FLIR images with complicated background. The algorithm is effective, robust and satisfied to real time tracking.

Untitled (Abstraction of Labour Time/ External Recurrence/Monad)

Commissioned print. Artist of the Month Club: February, 2010. January Curator: Mark Beasley. Invisible Exports Gallery, New York. Archival Inkjet Print on metallic silver polyester, 841 x 643mm. Edition of 50 + 10ap. Subsequently exhibited in the following exhibition: 'A Unicorn Basking in the Light of Three Glowing Suns' The Devos Art Museum School of Art & Design at Northern Michigan University October 8 – November 14, 2010 Curated by Anthony Elms and Philip von Zweck

Untitled (Abstraction of labour time eternal recurrence monad)

An AHRC funded project titled: Picturing ideas? Visualising and Synthesising Ideas as art (2009-10). Outputs including: 4 exhibitions; 4 publications; 3 papers; 2 largescale backlit digital prints; 1 commissioned print. (See Additional Information) ----ABSTRACT: Utilising the virtuality of digital imagery this practice-led project explored the possibility of the cross-articulation between text and image and the bridging or synthesising potential of the visual affect of ideas. A series of digital images were produced 'picturing' or 'visualising' philosophical ideas derived from the writings of the philosopher Giles Deleuze, as remodellings of pre-existing philosophical ideas; developed through dialogues and consultation with specialists in the fields from which the ideas were drawn (philosophy, psychology, film) as well as artists and theorists concerned with ideas of 'mental imagery' and visualisation. Final images were produced as a synthesis (or combination) of these visualisations and presented in the format of large scale, backlit digital prints at a series of prestigious international exhibitions (see details above). Evaluation took the form of a four page illustrated text in Frieze magazine (August 2009) and three papers delivered at University of Ulster, Goldsmiths College of Art and Loughborough University. The project also included the publication of a catalogue essay (EAST 09) and an illustrated poem (in the Dark Monarch publication). A print version of the image was commissioned by Invisible Exports Gallery, New York and subsequently exhibited in The Devos Art Museum, School of Art & Design at Northern Michigan University and in a publication edited by Cedar Lewisohn for Tate Publishing. The project was funded by an AHRC practice-led grant (17K) and Arts Council of England award (1.5K). The outputs, including high profile, publicly accessible exhibitions, prestigious publications and conference papers ensured the dissemination of the research to a wide range of audiences, including scholars/researchers across the arts and humanities engaged in practice-based and interdisciplinary theoretical work (in particular in the fields of contemporary art and art theory and those working on the integration of art and theory/philosophy/psychology) but also the wider audience for contemporary art.

Driving saccade to pursuit using image motion

Within the context of active vision, scant attention has been paid to the execution of motion saccades—rapid re-adjustments of the direction of gaze to attend to moving objects. In this paper we first develop a methodology for, and give real-time demonstrations of, the use of motion detection and segmentation processes to initiate capture saccades towards a moving object. The saccade is driven by both position and velocity of the moving target under the assumption of constant target velocity, using prediction to overcome the delay introduced by visual processing. We next demonstrate the use of a first order approximation to the segmented motion field to compute bounds on the time-to-contact in the presence of looming motion. If the bound falls below a safe limit, a panic saccade is fired, moving the camera away from the approaching object. We then describe the use of image motion to realize smooth pursuit, tracking using velocity information alone, where the camera is moved so as to null a single constant image motion fitted within a central image region. Finally, we glue together capture saccades with smooth pursuit, thus effecting changes in both what is being attended to and how it is being attended to. To couple the different visual activities of waiting, saccading, pursuing and panicking, we use a finite state machine which provides inherent robustness outside of visual processing and provides a means of making repeated exploration. We demonstrate in repeated trials that the transition from saccadic motion to tracking is more likely to succeed using position and velocity control, than when using position alone.

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy. The accuracy was reduced in urban areas partly because of TerraSAR-X’s restricted visibility of the ground surface due to radar shadow and layover.

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, classifying 89% of flooded pixels correctly, with an associated false positive rate of 6%. Of the urban water pixels visible to TerraSAR-X, 75% were correctly detected, with a false positive rate of 24%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 57% and 18% respectively.

Parallel pipelined array architectures for real-time histogram computation in consumer devices

The real-time parallel computation of histograms using an array of pipelined cells is proposed and prototyped in this paper with application to consumer imaging products. The array operates in two modes: histogram computation and histogram reading. The proposed parallel computation method does not use any memory blocks. The resulting histogram bins can be stored into an external memory block in a pipelined fashion for subsequent reading or streaming of the results. The array of cells can be tuned to accommodate the required data path width in a VLSI image processing engine as present in many imaging consumer devices. Synthesis of the architectures presented in this paper in FPGA are shown to compute the real-time histogram of images streamed at over 36 megapixels at 30 frames/s by processing in parallel 1, 2 or 4 pixels per clock cycle.

Coping with delays for real-time gaze control (The Fall and Rise of the Smiths Regulator)

In this paper we describe how to cope with the delays inherent in a real time control system for a steerable stereo head/eye platform. A purposive and reactive system requires the use of fast vision algorithms to provide the controller with the error signals to drive the platform. The time-critical implementation of these algorithms is necessary, not only to enable short latency reaction to real world events, but also to provide sufficiently high frequency results with small enough delays that controller remain stable. However, even with precise knowledge of that delay, nonlinearities in the plant make modelling of that plant impossible, thus precluding the use of a Smith Regulator. Moreover, the major delay in the system is in the feedback (image capture and vision processing) rather than feed forward (controller) loop. Delays ranging between 40msecs and 80msecs are common for the simple 2D processes, but might extend to several hundred milliseconds for more sophisticated 3D processes. The strategy presented gives precise control over the gaze direction of the cameras despite the lack of a priori knowledge of the delays involved. The resulting controller is shown to have a similar structure to the Smith Regulator, but with essential modifications.

Reactions to peripheral image motion using a head/eye platform

The authors demonstrate four real-time reactive responses to movement in everyday scenes using an active head/eye platform. They first describe the design and realization of a high-bandwidth four-degree-of-freedom head/eye platform and visual feedback loop for the exploration of motion processing within active vision. The vision system divides processing into two scales and two broad functions. At a coarse, quasi-peripheral scale, detection and segmentation of new motion occurs across the whole image, and at fine scale, tracking of already detected motion takes place within a foveal region. Several simple coarse scale motion sensors which run concurrently at 25 Hz with latencies around 100 ms are detailed. The use of these sensors are discussed to drive the following real-time responses: (1) head/eye saccades to moving regions of interest; (2) a panic response to looming motion; (3) an opto-kinetic response to continuous motion across the image and (4) smooth pursuit of a moving target using motion alone.

A flow system for the on-line quantitative measurement of the retention of dosage forms on biological surfaces using spectroscopy and image analysis

Measuring the retention, or residence time, of dosage forms to biological tissue is commonly a qualitative measurement, where no real values to describe the retention can be recorded. The result of this is an assessment that is dependent upon a user's interpretation of visual observation. This research paper outlines the development of a methodology to quantitatively measure, both by image analysis and by spectrophotometric techniques, the retention of material to biological tissues, using the retention of polymer solutions to ocular tissue as an example. Both methods have been shown to be repeatable, with the spectrophotometric measurement generating data reliably and quickly for further analysis.

Automatic near real-time selection of flood water levels from high resolution Synthetic Aperture Radar images for assimilation into hydraulic models: a case study

Flood extents caused by fluvial floods in urban and rural areas may be predicted by hydraulic models. Assimilation may be used to correct the model state and improve the estimates of the model parameters or external forcing. One common observation assimilated is the water level at various points along the modelled reach. Distributed water levels may be estimated indirectly along the flood extents in Synthetic Aperture Radar (SAR) images by intersecting the extents with the floodplain topography. It is necessary to select a subset of levels for assimilation because adjacent levels along the flood extent will be strongly correlated. A method for selecting such a subset automatically and in near real-time is described, which would allow the SAR water levels to be used in a forecasting model. The method first selects candidate waterline points in flooded rural areas having low slope. The waterline levels and positions are corrected for the effects of double reflections between the water surface and emergent vegetation at the flood edge. Waterline points are also selected in flooded urban areas away from radar shadow and layover caused by buildings, with levels similar to those in adjacent rural areas. The resulting points are thinned to reduce spatial autocorrelation using a top-down clustering approach. The method was developed using a TerraSAR-X image from a particular case study involving urban and rural flooding. The waterline points extracted proved to be spatially uncorrelated, with levels reasonably similar to those determined manually from aerial photographs, and in good agreement with those of nearby gauges.

The time course of implicit affective picture processing: an eye movement study

Consistent with a negativity bias account, neuroscientific and behavioral evidence demonstrates modulation of even early sensory processes by unpleasant, potentially threat-relevant information. The aim of this research is to assess the extent to which pleasant and unpleasant visual stimuli presented extrafoveally capture attention and impact eye movement control. We report an experiment examining deviations in saccade metrics in the presence of emotional image distractors that are close to a nonemotional target. We additionally manipulate the saccade latency to test when the emotional distractor has its biggest impact on oculomotor control. The results demonstrate that saccade landing position was pulled toward unpleasant distractors, and that this pull was due to the quick saccade responses. Overall, these findings support a negativity bias account of early attentional control and call for the need to consider the time course of motivated attention when affect is implicit

ATD: a multiplatform for semiautomatic 3-D detection of kidneys and their pathology in real time

This research presents a novel multi-functional system for medical Imaging-enabled Assistive Diagnosis (IAD). Although the IAD demonstrator has focused on abdominal images and supports the clinical diagnosis of kidneys using CT/MRI imaging, it can be adapted to work on image delineation, annotation and 3D real-size volumetric modelling of other organ structures such as the brain, spine, etc. The IAD provides advanced real-time 3D visualisation and measurements with fully automated functionalities as developed in two stages. In the first stage, via the clinically driven user interface, specialist clinicians use CT/MRI imaging datasets to accurately delineate and annotate the kidneys and their possible abnormalities, thus creating “3D Golden Standard Models”. Based on these models, in the second stage, clinical support staff i.e. medical technicians interactively define model-based rules and parameters for the integrated “Automatic Recognition Framework” to achieve results which are closest to that of the clinicians. These specific rules and parameters are stored in “Templates” and can later be used by any clinician to automatically identify organ structures i.e. kidneys and their possible abnormalities. The system also supports the transmission of these “Templates” to another expert for a second opinion. A 3D model of the body, the organs and their possible pathology with real metrics is also integrated. The automatic functionality was tested on eleven MRI datasets (comprising of 286 images) and the 3D models were validated by comparing them with the metrics from the corresponding “3D Golden Standard Models”. The system provides metrics for the evaluation of the results, in terms of Accuracy, Precision, Sensitivity, Specificity and Dice Similarity Coefficient (DSC) so as to enable benchmarking of its performance. The first IAD prototype has produced promising results as its performance accuracy based on the most widely deployed evaluation metric, DSC, yields 97% for the recognition of kidneys and 96% for their abnormalities; whilst across all the above evaluation metrics its performance ranges between 96% and 100%. Further development of the IAD system is in progress to extend and evaluate its clinical diagnostic support capability through development and integration of additional algorithms to offer fully computer-aided identification of other organs and their abnormalities based on CT/MRI/Ultra-sound Imaging.