Moving-edge detection via heat flow analogy

In this paper, a new and automatic moving-edge detection algorithm is proposed, based on using the heat flow analogy. This algorithm starts with anisotropic heat diffusion in the spatial domain, to remove noise and sharpen region boundaries for the purpose of obtaining high quality edge data. Then, isotropic and linear heat diffusion is applied in the temporal domain to calculate the total amount of heat flow. The moving-edges are represented as the total amount of heat flow out from the reference frame. The overall process is completed by non-maxima suppression and hysteresis thresholding to obtain binary moving edges. Evaluation, on a variety of data, indicates that this approach can handle noise in the temporal domain because of the averaging inherent of isotropic heat flow. Results also show that this technique can detect moving-edges in image sequences, without background image subtraction

On Using Physical Analogies for Feature and Shape Extraction in Computer Vision

There is a rich literature of approaches to image feature extraction in computer vision. Many sophisticated approaches exist for low- and for high-level feature extraction but can be complex to implement with parameter choice guided by experimentation, but with performance analysis and optimization impeded by speed of computation. We have developed new feature extraction techniques on notional use of physical paradigms, with parametrization aimed to be more familiar to a scientifically trained user, aiming to make best use of computational resource. This paper is the first unified description of these new approaches, outlining the basis and results that can be achieved. We describe how gravitational force can be used for low-level analysis, while analogies of water flow and heat can be deployed to achieve high-level smooth shape detection, by determining features and shapes in a selection of images, comparing results with those by stock approaches from the literature. We also aim to show that the implementation is consistent with the original motivations for these techniques and so contend that the exploration of physical paradigms offers a promising new avenue for new approaches to feature extraction in computer vision

In-situ steel solidification imaging in continuous casting using magnetic induction tomography

: Solidification process in continuous casting is a critical part of steel production. The speed and quality of the solidification process determines the quality of final product. Computational fluid dynamics (CFD) simulations are often used to describe the process and design of its control system, but so far, there is no any tool that provides an on-line measurement of the solidification front of hot steel during the continuous casting process. This paper presents a new tool based on magnetic induction tomography (MIT) for real time monitoring of this process. The new MIT system was installed at the end of the secondary cooling chamber of a casting unit and tested during several days in a real production process. MIT is able to create an internal map of electrical conductivity of hot steel deep inside the billet. The image of electrical conductivity is then converted to temperature profile that allows the measurement of the solid, mushy and liquid layers. In this study, such a conversion is done by synchronizing in one time step the MIT measurement and the thermal map generated with the actual process parameters available at that time. The MIT results were then compared with the results obtained of the CFD and thermal modelling of the industrial process. This is the first in-situ monitoring of the interior structure during a real continuous casting.The SHELL-THICK project has received funding from EU Research Fund for Coal and Steel under grant number 709830. This study reflects only the author's views and the European Commission is not responsible for any use that may be made of the information contained therein

XMM-Newton observations of the Galactic Centre Region - II: The soft thermal emission

We have extended our earlier study (Heard & Warwick 2013, Paper I) of the X-ray emission emanating from the central 100 pc x 100 pc region of our Galaxy to an investigation of several features prominent in the soft X-ray (2-4.5 keV) band. We focus on three specific structures: a putative bipolar outflow from the vicinity of Sgr A*; a high surface brightness region located roughly 12 arcmin to the north-east of Sgr A*; and a lower surface-brightness extended loop feature seen to the south of Sgr A*. We show that all three structures are thermal in nature and have similar temperatures (kT ~ 1 keV). The inferred X-ray luminosities lie in the range (2 - 10) x 10^34 erg s^-1. In the case of the bipolar feature we suggest that the hot plasma is produced by the shock-heating of the winds from massive stars within the Central Cluster, possibly collimated by the Circumnuclear Disc. Alternatively the outflow may be driven by outbursts on Sgr A*, which follow tidal disruption events occurring at a rate of roughly 1 every 4000 yr. The north-east enhancement is centred on a candidate PWN which has a relatively hard non-thermal X-ray spectrum. We suggest that the coincident soft-thermal emission traces the core of a new thermal-composite supernova remnant, designated as SNR G0.13-0.12. There is no clear evidence for an associated radio shell but such a feature may be masked by the bright emission of the nearby Radio Arc and other filamentary structures. SNR G0.13-0.12 is very likely interacting with the nearby molecular cloud, G0.11-0.11, and linked to the Fermi source, 2FGL J1746.4-2851c. Finally we explore a previous suggestion that the elliptically-shaped X-ray loop to the south of Sgr A*, of maximum extent ~45 pc, represents the shell of a superbubble located in the GC region. Although plausible, the interpretation of this feature in terms a coherent physical structure awaits confirmation.Comment: 17 pages, 6 figures, accepted for publication in MNRA

Chandra Early-Type Galaxy Atlas

The hot ISM in early type galaxies (ETGs) plays a crucial role in understanding their formation and evolution. The structural features of the hot gas identified by Chandra observations point to key evolutionary mechanisms, (e.g., AGN and stellar feedback, merging history). In our Chandra Galaxy Atlas (CGA) project, taking full advantage of the Chandra capabilities, we systematically analyzed the archival Chandra data of 70 ETGs and produced uniform data products for the hot gas properties. The primary data products are spatially resolved 2D spectral maps of the hot gas from individual galaxies. We emphasize that new features can be identified in the spectral maps which are not readily visible in the surface brightness maps. The high-level images can be viewed at the dedicated CGA website, and the CGA data products can be downloaded to compare with data at other wavelengths and to perform further analyses. Utilizing our data products, we address a few focused science topics.Comment: 52 pages, 9 figures, accepted in ApJ Supp