Custom coprocessor based matrix algorithms for image and signal processing

Matrix algorithms are important in many types of applications including image and signal processing. A close examination of the algorithms used in these, and related, applications reveals that many of the fundamental actions involve matrix algorithms such as matrix multiplication. This paper presents an investigation into the design and implementation of different matrix algorithms such as matrix operations, matrix transforms and matrix decompositions using a novel custom coprocessor system for MATrix algorithms based on Reconfigurable Computing (RCMAT). The proposed RCMAT architectures are scalable, modular and require less area and time complexity with reduced latency when compared with existing structures.

Playful structure: a novel image of early years pedagogy for primary school classrooms

Playful structure is a new pedagogic image representing a more balanced and integrated perspective on early years pedagogy, aiming to blend apparent dichotomies and contradictions and to sustain and evolve play-based practice beyond Year 1. Playful structure invites teachers and children to initiate and maintain a degree of playfulness in the child’s whole learning experience, even when the learning intentions demand a supportive structure. Thus, playfulness becomes characteristic of the interaction between adult and the child and not just characteristic of child-initiated versus adult-initiated activities, or of play-time versus task-time. The paper is based on intensive observations and interviews with teachers in Northern Ireland who participated in a play-based and informal curriculum. This paper explains how playful structure rests on complementary processes of infusion of structure into play-based activities and infusion of playfulness into more structured activities, illustrated by cameos. ‘Infusion’ suggests the subtle blending process that allows apparent dichotomies and contradictions to be resolved in practice.

Image processing chip for small object detection

A new, front-end image processing chip is presented for real-time small object detection. It has been implemented using a 0.6 µ, 3.3 V CMOS technology and operates on 10-bit input data at 54 megasamples per second. It occupies an area of 12.9 mm×13.6 mm (including pads), dissipates 1.5 W, has 92 I/O pins and is to be housed in a 160-pin ceramic quarter flat-pack. It performs both one- and two-dimensional FIR filtering and a multilayer perceptron (MLP) neural network function using a reconfigurable array of 21 multiplication-accumulation cells which corresponds to a window size of 7×3. The chip can cope with images of 2047 pixels per line and can be cascaded to cope with larger window sizes. The chip performs two billion fixed point multiplications and additions per second.

Androgen deprivation results in time-dependent hypoxia in LNCaP prostate tumours; informed scheduling of the bioreductive drug AQ4N improves treatment response

Androgen withdrawal induces hypoxia in androgen-sensitive tissue; this is important as in the tumour microenvironment hypoxia is known to drive malignant progression. This study examined the time-dependent effect of androgen deprivation therapy (ADT) on tumour oxygenation and investigated the role of ADT-induced hypoxia on malignant progression in prostate tumours. LNCaP xenografted tumours were treated with anti-androgens and tumour oxygenation measured. Dorsal skin fold chambers (DSF) were used to image tumour vasculature in vivo. Quantitative PCR (QPCR) identified differential gene expression following treatment with bicalutamide. Bicalutamide and vehicle-only treated tumours were re-established in vitro and invasion and sensitivity to docetaxel were measured. Tumour growth delay was calculated following treatment with bicalutamide combined with the bioreductive drug AQ4N. Tumour oxygenation measurements showed a precipitate decrease following initiation of ADT. A clinically relevant dose of bicalutamide (2mg/kg/day) decreased tumour oxygenation by 45% within 24h, reaching a nadir of 0.09% oxygen (0.67±0.06 mmHg) by day 7; this persisted until day 14 when it increased up to day 28. Using DSF chambers, LNCaP tumours treated with bicalutamide showed loss of small vessels at days 7 and 14 with revascularization occurring by day 21. QPCR showed changes in gene expression consistent with the vascular changes and malignant progression. Cells from bicalutamide-treated tumours were more malignant than vehicle-treated controls. Combining bicalutamide with AQ4N (50mg/kg; single dose) caused greater tumour growth delay than bicalutamide alone. This study shows that bicalutamide-induced hypoxia selects for cells that show malignant progression; targeting hypoxic cells may provide greater clinical benefit.

Microstructural analysis of non-woven fabrics using scanning electron microscopy and image processing. Part 1:Development and verification of the methods

This paper reports image analysis methods that have been developed to study the microstructural changes of non-wovens made by the hydroentanglement process. The validity of the image processing techniques has been ascertained by applying them to test images with known properties. The parameters in preprocessing of the scanning electron microscope (SEM) images used in image processing have been tested and optimized. The fibre orientation distribution is estimated using fast Fourier transform (FFT) and Hough transform (HT) methods. The results obtained using these two methods are in good agreement. The HT method is more demanding in computational time compared with the Fourier transform (FT) method. However, the advantage of the HT method is that the actual orientation of the lines can be concluded directly from the result of the transform without the need for any further computation. The distribution of the length of the straight fibre segments of the fabrics is evaluated by the HT method. The effect of curl of the fibres on the result of this evaluation is shown.

IPPro: FPGA based Image Processing Processor

The paper presents IPPro which is a high performance, scalable soft-core processor targeted for image processing applications. It has been based on the Xilinx DSP48E1 architecture using the ZYNQ Field Programmable Gate Array and is a scalar 16-bit RISC processor that operates at 526MHz, giving 526MIPS of performance. Each IPPro core uses 1 DSP48, 1 Block RAM and 330 Kintex-7 slice-registers, thus making the processor as compact as possible whilst maintaining flexibility and programmability. A key aspect of the approach is in reducing the application design time and implementation effort by using multiple IPPro processors in a SIMD mode. For different applications, this allows us to exploit different levels of parallelism and mapping for the specified processing architecture with the supported instruction set. In this context, a Traffic Sign Recognition (TSR) algorithm has been prototyped on a Zedboard with the colour and morphology operations accelerated using multiple IPPros. Simulation and experimental results demonstrate that the processing platform is able to achieve a speedup of 15 to 33 times for colour filtering and morphology operations respectively, with a reduced design effort and time.

Use of Short Time-on-Stream Attenuated Total Internal Reflection Infrared Spectroscopy To Probe Changes in Adsorption Geometry for Determination of Selectivity in the Hydrogenation of Citral

Abstract Image

A new experimental procedure based on attenuated total reflection infrared spectroscopy has been developed to investigate surface species under liquid phase reaction conditions. The technique has been tested by investigating the enhanced selectivity in the hydrogenation of α,β-unsaturated aldehyde citral over a 5% Pt/SiO2 catalyst toward unsaturated alcohols geraniol/nerol, which occurs when citronellal is added to the reaction. The change in selectivity is proposed to be the result of a change in the citral adsorption mode in the presence of citronellal. Short time on stream attenuated total internal reflection infrared spectroscopy has allowed identification of the adsorption modes of citral. With no citronellal, citral adsorbs through both the C═C and C═O groups; however, in the presence of citronellal, citral adsorption occurs through the C═O group only, which is proposed to be the cause of the altered reaction selectivity.

Dataflow toolset for soft-core processors on FPGA for image processing applications

With security and surveillance, there is an increasing need to be able to process image data efficiently and effectively either at source or in a large data networks. Whilst Field Programmable Gate Arrays have been seen as a key technology for enabling this, they typically use high level and/or hardware description language synthesis approaches; this provides a major disadvantage in terms of the time needed to design or program them and to verify correct operation; it considerably reduces the programmability capability of any technique based on this technology. The work here proposes a different approach of using optimised soft-core processors which can be programmed in software. In particular, the paper proposes a design tool chain for programming such processors that uses the CAL Actor Language as a starting point for describing an image processing algorithm and targets its implementation to these custom designed, soft-core processors on FPGA. The main purpose is to exploit the task and data parallelism in order to achieve the same parallelism as a previous HDL implementation but avoiding the design time, verification and debugging steps associated with such approaches.

Optimizing geometric accuracy of four dimensional CT scans acquired using the wall and couch mounted Varian Real-Time Position Management camera systems

Objective:

The aim of this study was to identify sources of anatomical misrepresentation due to the location of camera mounting, tumour motion velocity and image processing artefacts in order to optimise the 4DCT scan protocol and improve geometrical-temporal accuracy.

A phantom with an imaging insert was driven with a sinusoidal superior-inferior motion of varying amplitude and period for 4DCT scanning. The length of a high density cube within the insert was measured using treatment planning software to determine the accuracy of its spatial representation. Scan parameters were varied including the tube rotation period and the cine time between reconstructed images. A CT image quality phantom was used to measure various image quality signatures under the scan parameters tested.

No significant difference in spatial accuracy was found for 4DCT scans carried out using the wall mounted or couch mounted camera for sinusoidal target motion. Greater spatial accuracy was found for 4DCT scans carried out using a tube rotation speed of 0.5s rather than 1.0s. The reduction in image quality when using a faster rotation speed was not enough to require an increase in patient dose.

4DCT accuracy may be increased by optimising scan parameters, including choosing faster tube rotation speeds. Peak misidentification in the recorded breathing trace leads to spatial artefacts and this risk can be reduced by using a couch mounted infrared camera.

This study explicitly shows that 4DCT scan accuracy is improved by scanning with a faster CT tube rotation speed.

Evolution of Hot Loops in an Active Region Core Observed with the SDO Atmospheric Image Assembly

Evidence has accumulated of high temperature (> 4 MK) coronal emission in active region cores that corresponds to structures in equilibrium. Other studies have found evidence of evolving loops. We investigate the EUV intensity and temperature variations of short coronal loops observed in the core of NOAA Active Region 11250 on 13 July 2011. The loops, which run directly between the AR opposite polarities, are first detectable in the 94Å band of Fe XVIII, implying an effective temperature ~ 7 MK. The low temperature component of the 94 Å signal is modeled in terms of a linear superposition of the 193 Å and 171 Å signals in order to separate the hot component. After identifying the loops we have used contemporaneous HMI observations to identify the corresponding inter-moss regions, and we have investigated their time evolution in six AIA EUV channels. The results can be separated into two classes. Group 1 (94Å, 335Å, 211Å) is characterized by hotter temperatures (~2-7 MK), and Group 2 (193Å, 171Å, 131Å) by cooler temperatures (0.4 - 1.6 MK). For Group 1 the intensity peaks in the 94Å channel are followed by maxima in the 335 Å channel with a time lag of ~8 min, suggestive of a cooling pattern with an exponential decay. While the 211Å maxima follow those in the 335 Å channel, there is no systematic relation which would indicate a progressive cooling process through the lower temperatures, as has been observed in other investigations. In Group 2 the signals in the 171 and 131Å channels track each other closely, and lag behind the 193Å. In the inter-moss region of the loop the peak temperature and peak emission measure have opposite trends. The hot 94Å brightenings occur in the central part of the loops with maximum temperatures ~7 MK. Subsequently the loops appear to fill with plasma with an emission measure compatible with the 193 Å signal and temperature in the range ~ 1.5-2 MK. Although the exact details of the time evolution are still under investigation, these non static loops show high levels of intermittency in the 94Å signal (please see poster "Intermittent and Scale-Invariant Intensity Fluctuations in Hot Coronal Loops," by Lawrence et al. in this session).

Selection of burst-like transients and stochastic variables using multi-brand image differencing in the Pan-STARRS1 Medium Deep Survey

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands gP1, rP1, iP1, and zP1. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 AGNs and 812 SNe. With these two samples, we characterize their variability and host galaxy properties, and identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys.

The host galaxy and late-time evolution of the superluminous supernova PTF12dam

Superluminous supernovae (SLSNe) of Type Ic have a tendency to occur in faint host galaxies which are likely to have low mass and low metallicity. PTF12dam is one of the closest and best-studied superluminous explosions that has a broad and slowly fading light curve similar to SN 2007bi. Here we present new photometry and spectroscopy for PTF12dam from 200-500 d (rest frame) after peak and a detailed analysis of the host galaxy (SDSS J142446.21+461348.6 at z = 0.107). Using deep templates and image subtraction we show that the light curve can be fit with a magnetar model if escape of high-energy gamma rays is taken into account. The full bolometric light curve from -53 to +399 d (with respect to peak) cannot be fit satisfactorily with the pair-instability models. An alternative model of interaction with a dense circumstellar material (CSM) produces a good fit to the data although this requires a very large mass (˜13 M⊙) of hydrogen-free CSM. The host galaxy is a compact dwarf (physical size ˜1.9 kpc) and with Mg = -19.33 ± 0.10, it is the brightest nearby SLSN Ic host discovered so far. The host is a low-mass system (2.8 × 108 M⊙) with a star formation rate (5.0 M⊙ yr-1), which implies a very high specific star formation rate (17.9 Gyr-1). The remarkably strong nebular emission provide detections of the [O III] λ4363 and [O II] λλ7320, 7330auroral lines and an accurate oxygen abundance of 12 + log (O/H) = 8.05 ± 0.09. We show here that they are at the extreme end of the metallicity distribution of dwarf galaxies and propose that low metallicity is a requirement to produce these rare and peculiar SNe.

Accurate image capturing control of bottle caps based on iterative learning control and Kalman filtering

This paper investigates camera control for capturing bottle cap target images in the fault-detection system of an industrial production line. The main purpose is to identify the targeted bottle caps accurately in real time from the images. This is achieved by combining iterative learning control and Kalman filtering to reduce the effect of various disturbances introduced into the detection system. A mathematical model, together with a physical simulation platform is established based on the actual production requirements, and the convergence properties of the model are analyzed. It is shown that the proposed method enables accurate real-time control of the camera, and further, the gain range of the learning rule is also obtained. The numerical simulation and experimental results confirm that the proposed method can not only reduce the effect of repeatable disturbances but also non-repeatable ones.

Streaming Elements for FPGA Signal and Image Processing Accelerators

Field programmable gate array devices boast abundant resources with which custom accelerator components for signal, image and data processing may be realised; however, realising high performance, low cost accelerators currently demands manual register transfer level design. Software-programmable ’soft’ processors have been proposed as a way to reduce this design burden but they are unable to support performance and cost comparable to custom circuits. This paper proposes a new soft processing approach for FPGA which promises to overcome this barrier. A high performance, fine-grained streaming processor, known as a Streaming Accelerator Element, is proposed which realises accelerators as large scale custom multicore networks. By adopting a streaming execution approach with advanced program control and memory addressing capabilities, typical program inefficiencies can be almost completely eliminated to enable performance and cost which are unprecedented amongst software-programmable solutions. When used to realise accelerators for fast fourier transform, motion estimation, matrix multiplication and sobel edge detection it is shown how the proposed architecture enables real-time performance and with performance and cost comparable with hand-crafted custom circuit accelerators and up to two orders of magnitude beyond existing soft processors.

FPGA based Streaming Image Processing Processor (SIPPro) architecture to accelerate data intensive applications

Current data-intensive image processing applications push traditional embedded architectures to their limits. FPGA based hardware acceleration is a potential solution but the programmability gap and time consuming HDL design flow is significant. The proposed research approach to develop “FPGA based programmable hardware acceleration platform” that uses, large number of Streaming Image processing Processors (SIPPro) potentially addresses these issues. SIPPro is pipelined in-order soft-core processor architecture with specific optimisations for image processing applications. Each SIPPro core uses 1 DSP48, 2 Block RAMs and 370 slice-registers, making the processor as compact as possible whilst maintaining flexibility and programmability. It is area efficient, scalable and high performance softcore architecture capable of delivering 530 MIPS per core using Xilinx Zynq SoC (ZC7Z020-3). To evaluate the feasibility of the proposed architecture, a Traffic Sign Recognition (TSR) algorithm has been prototyped on a Zedboard with the color and morphology operations accelerated using multiple SIPPros. Simulation and experimental results demonstrate that the processing platform is able to achieve a speedup of 15 and 33 times for color filtering and morphology operations respectively, with a significant reduced design effort and time.