A stochastic dynamical system for image segmentation

Image segmentation is formulated as a stochastic process whose invariant distribution is concentrated at points of the desired region. By choosing multiple seed points, different regions can be segmented. The algorithm is based on the theory of time-homogeneous Markov chains and has been largely motivated by the technique of simulated annealing. The method proposed here has been found to perform well on real-world clean as well as noisy images while being computationally far less expensive than stochastic optimisation techniques

Image Encryption with Space-filling Curves

Conventional encryption techniques are usually applicable for text data and often unsuited for encrypting multimedia objects for two reasons. Firstly, the huge sizes associated with multimedia objects make conventional encryption computationally costly. Secondly, multimedia objects come with massive redundancies which are useful in avoiding encryption of the objects in their entirety. Hence a class of encryption techniques devoted to encrypting multimedia objects like images have been developed. These techniques make use of the fact that the data comprising multimedia objects like images could in general be seggregated into two disjoint components, namely salient and non-salient. While the former component contributes to the perceptual quality of the object, the latter only adds minor details to it. In the context of images, the salient component is often much smaller in size than the non-salient component. Encryption effort is considerably reduced if only the salient component is encrypted while leaving the other component unencrypted. A key challenge is to find means to achieve a desirable seggregation so that the unencrypted component does not reveal any information about the object itself. In this study, an image encryption approach that uses fractal structures known as space-filling curves- in order to reduce the encryption overload is presented. In addition, the approach also enables a high quality lossy compression of images.

Particle image velocimetry and infrared thermography in a levitated droplet with nanosilica suspensions

Preferential accumulation and agglomeration kinetics of nanoparticles suspended in an acoustically levitated water droplet under radiative heating has been studied. Particle image velocimetry performed to map the internal flow field shows a single cell recirculation with increasing strength for decreasing viscosities. Infrared thermography and high speed imaging show details of the heating process for various concentrations of nanosilica droplets. Initial stage of heating is marked by fast vaporization of liquid and sharp temperature rise. Following this stage, aggregation of nanoparticles is seen resulting in various structure formations. At low concentrations, a bowl structure of the droplet is dominant, maintained at a constant temperature. At high concentrations, viscosity of the solution increases, leading to rotation about the levitator axis due to the dominance of centrifugal motion. Such complex fluid motion inside the droplet due to acoustic streaming eventually results in the formation of a ring structure. This horizontal ring eventually reorients itself due to an imbalance of acoustic forces on the ring, exposing larger area for laser absorption and subsequent sharp temperature rise.

Three-Component Self-Assembly of a Series of Triply Interlocked Pd12 Coordination Prisms and Their Non-Interlocked Pd6 Analogues

Template-assisted formation of multicomponent Pd6 coordination prisms and formation of their self-templated triply interlocked Pd12 analogues in the absence of an external template have been established in a single step through Pd?N/Pd?O coordination. Treatment of cis-[Pd(en)(NO3)2] with K3tma and linear pillar 4,4'-bpy (en=ethylenediamine, H3tma=benzene-1,3,5-tricarboxylic acid, 4,4'-bpy=4,4'-bipyridine) gave intercalated coordination cage [{Pd(en)}6(bpy)3(tma)2]2[NO3]12 (1) exclusively, whereas the same reaction in the presence of H3tma as an aromatic guest gave a H3tma-encapsulating non-interlocked discrete Pd6 molecular prism [{Pd(en)}6(bpy)3(tma)2(H3tma)2][NO3]6 (2). Though the same reaction using cis-[Pd(NO3)2(pn)] (pn=propane-1,2-diamine) instead of cis-[Pd(en)(NO3)2] gave triply interlocked coordination cage [{Pd(pn)}6(bpy)3(tma)2]2[NO3]12 (3) along with non-interlocked Pd6 analogue [{Pd(pn)}6(bpy)3(tma)2](NO3)6 (3'), and the presence of H3tma as a guest gave H3tma-encapsulating molecular prism [{Pd(pn)}6(bpy)3(tma)2(H3tma)2][NO3]6 (4) exclusively. In solution, the amount of 3' decreases as the temperature is decreased, and in the solid state 3 is the sole product. Notably, an analogous reaction using the relatively short pillar pz (pz=pyrazine) instead of 4,4'-bpy gave triply interlocked coordination cage [{Pd(pn)}6(pz)3(tma)2]2[NO3]12 (5) as the single product. Interestingly, the same reaction using slightly more bulky cis-[Pd(NO3)2(tmen)] (tmen=N,N,N',N'-tetramethylethylene diamine) instead of cis-[Pd(NO3)2(pn)] gave non-interlocked [{Pd(tmen)}6(pz)3(tma)2][NO3]6 (6) exclusively. Complexes 1, 3, and 5 represent the first examples of template-free triply interlocked molecular prisms obtained through multicomponent self-assembly. Formation of the complexes was supported by IR and multinuclear NMR (1H and 13C) spectroscopy. Formation of guest-encapsulating complexes (2 and 4) was confirmed by 2D DOSY and ROESY NMR spectroscopic analyses, whereas for complexes 1, 3, 5, and 6 single-crystal X-ray diffraction techniques unambiguously confirmed their formation. The gross geometries of H3tma-encapsulating complexes 2 and 4 were obtained by universal force field (UFF) simulations.

A tracking-based general framework to image halftoning

Existing approches to digital halftoning of image are based primarily on thresholding. We propose a general framework fot image halftoning whcrc some function uf the output halftone tracks another function of the input gray-tone.This appcoach is shown lo unify most existing algorithms and to provide useful insights. Further, the new intcrpretation allows us to remedy problems in existing aigorithrms such as the error dlffusion, and sohsequently to achieve halftones haavmg superior quality. The proposed method is very general nature is an advantage since it offers a wide choice of three Cilters and a update rule. An intercstmg product of this framework is that equally good, or better, half-tones are possible ro be obtained by thresholding a noise proccess instead of the image itself.

Homo- or Heterosynthon? A Crystallographic Study on a Series of New Cocrystals Derived from Pyrazinecarboxamide and Various Carboxylic Acids Equipped with Additional Hydrogen Bonding Sites

Four new cocrystals of a well studied active pharmaceutical ingredient (API), namely, pyrazinecarboxamide (PZA), with various monocarboxylic acids equipped with additional hydrogen bonding sites such as vanillic acid (VA), gallic acid (GA), 1-hydroxy-2-naphthoic acid (1HNA), and indole-2-carboxylic acid (I2CA) have been successfully prepared and characterized by FTIR, H-1 NMR, differential scanning calorimetry (DSC), and single crystal and powder X-ray diffraction (SXRD and PXRD, respectively) techniques. In the majority of the cases, preferential occurrence amide amide and acid acid homosynthons has been observed. Since the heterosynthon is energetically preferred to homosynthon, such unusual occurrence of homosynthon in these cocrystals is intriguing.

Structure and deformation correlation of closed-cell aluminium foam subject to uniaxial compression

We report the results of an experimental and numerical study conducted on a closed-cell aluminium foam that was subjected to uniaxial compression with lateral constraint. X-ray computed tomography was utilized to gain access into the three-dimensional (3-D) structure of the foam and some aspects of the deformation mechanisms. A series of advanced 3-D image analyses are conducted on the 3-D images aimed at characterizing the strain localization regions. We identify the morphological/geometrical features that are responsible for the collapse of the cells and the strain localization. A novel mathematical approach based on a Minkowski tensor analysis along with the mean intercept length technique were utilized to search for signatures of anisotropy across the foam sample and its evolution as a function of loading. Our results show that regions with higher degrees of anisotropy in the undeformed foam have a tendency to initiate the onset of cell collapse. Furthermore, we show that strain hardening occurs predominantly in regions with large cells and high anisotropy. We combine the finite element method with the tomographic images to simulate the mechanical response of the foam. We predict further deformation in regions where the foam is already deformed. Crown Copyright (C) 2012 Published by Elsevier Ltd. on behalf of Acta Materialia Inc. All rights reserved.

Linearization and Reconstruction of Non-linear Diffuse Optical Tomographic Image

Diffuse optical tomography (DOT) is one of the ways to probe highly scattering media such as tissue using low-energy near infra-red light (NIR) to reconstruct a map of the optical property distribution. The interaction of the photons in biological tissue is a non-linear process and the phton transport through the tissue is modelled using diffusion theory. The inversion problem is often solved through iterative methods based on nonlinear optimization for the minimization of a data-model misfit function. The solution of the non-linear problem can be improved by modeling and optimizing the cost functional. The cost functional is f(x) = x(T)Ax - b(T)x + c and after minimization, the cost functional reduces to Ax = b. The spatial distribution of optical parameter can be obtained by solving the above equation iteratively for x. As the problem is non-linear, ill-posed and ill-conditioned, there will be an error or correction term for x at each iteration. A linearization strategy is proposed for the solution of the nonlinear ill-posed inverse problem by linear combination of system matrix and error in solution. By propagating the error (e) information (obtained from previous iteration) to the minimization function f(x), we can rewrite the minimization function as f(x; e) = (x + e)(T) A(x + e) - b(T)(x + e) + c. The revised cost functional is f(x; e) = f(x) + e(T)Ae. The self guided spatial weighted prior (e(T)Ae) error (e, error in estimating x) information along the principal nodes facilitates a well resolved dominant solution over the region of interest. The local minimization reduces the spreading of inclusion and removes the side lobes, thereby improving the contrast, localization and resolution of reconstructed image which has not been possible with conventional linear and regularization algorithm.

Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data

Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called `early warning signals', and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data.

A Series of Trifacial Pd6 Molecular Barrels with Porphyrin Walls

Three new nanoscopic trigonal prisms, (tmen)6Pd6(H2L)3](NO3)12 (1), (Meen)6Pd6(H2L)3](NO3)12 (2), and (2,2'-bipy)6Pd6(H2L)3](NO3)12 (3), have been synthesized in excellent yields through single-step metalligand-coordination-driven self-assembly using 5,10,15,20-tetrakis(3-pyridyl)porphyrin (H2L) as a donor and cis-blocked PdII 90 degrees acceptors. These complexes were fully characterized by spectroscopic studies and single-crystal X-ray diffraction. All of these barrels quantitatively bind ZnII ions in the N4 pockets of the porphyrin walls at room temperature. Their corresponding zinc-embedded complexes, (tmen)6Pd6(ZnL)3](NO3)12 (1?a), (Meen)6Pd6(ZnL)3](NO3)12 (2?a), and (2,2'-bipy)6Pd6(ZnL)3](NO3)12 (3?a), were synthesized under ambient conditions by the post-synthetic binding of ZnII ions into the H2N4 pockets of the porphyrin walls of these complexes. These zinc-embedded complexes were characterized by electronic absorption, fluorescence emission, 1H NMR spectroscopy, as well as elemental analysis. Complexes 13 exhibited considerable microporosity in their solid state. Complex 1 was an efficient adsorbent for nitrogen gas and EtOH, MeOH, and water vapors.

Fast image reconstruction for fluorescence microscopy

Real-time image reconstruction is essential for improving the temporal resolution of fluorescence microscopy. A number of unavoidable processes such as, optical aberration, noise and scattering degrade image quality, thereby making image reconstruction an ill-posed problem. Maximum likelihood is an attractive technique for data reconstruction especially when the problem is ill-posed. Iterative nature of the maximum likelihood technique eludes real-time imaging. Here we propose and demonstrate a compute unified device architecture (CUDA) based fast computing engine for real-time 3D fluorescence imaging. A maximum performance boost of 210x is reported. Easy availability of powerful computing engines is a boon and may accelerate to realize real-time 3D fluorescence imaging. Copyright 2012 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. http://dx.doi.org/10.1063/1.4754604]

Prior image-constrained l(1)-norm-based reconstruction method for effective usage of structural information in diffuse optical tomography

A novel approach that can more effectively use the structural information provided by the traditional imaging modalities in multimodal diffuse optical tomographic imaging is introduced. This approach is based on a prior image-constrained-l(1) minimization scheme and has been motivated by the recent progress in the sparse image reconstruction techniques. It is shown that the proposed framework is more effective in terms of localizing the tumor region and recovering the optical property values both in numerical and gelatin phantom cases compared to the traditional methods that use structural information. (C) 2012 Optical Society of America

Effective contrast recovery in rapid dynamic near-infrared diffuse optical tomography using l(1)-norm-based linear image reconstruction method

Traditional image reconstruction methods in rapid dynamic diffuse optical tomography employ l(2)-norm-based regularization, which is known to remove the high-frequency components in the reconstructed images and make them appear smooth. The contrast recovery in these type of methods is typically dependent on the iterative nature of method employed, where the nonlinear iterative technique is known to perform better in comparison to linear techniques (noniterative) with a caveat that nonlinear techniques are computationally complex. Assuming that there is a linear dependency of solution between successive frames resulted in a linear inverse problem. This new framework with the combination of l(1)-norm based regularization can provide better robustness to noise and provide better contrast recovery compared to conventional l(2)-based techniques. Moreover, it is shown that the proposed l(1)-based technique is computationally efficient compared to its counterpart (l(2)-based one). The proposed framework requires a reasonably close estimate of the actual solution for the initial frame, and any suboptimal estimate leads to erroneous reconstruction results for the subsequent frames.

Natural convection in a series of thermally interacting cavities with wall mounted heaters

Laminar natural convection in a series of thermally interacting cavities is numerically studied. Each cavity consists of a conducting bottom wall with a surface mounted heater. The side walls of the cavities are isothermally cooled. Each cavity thermally interacts with its adjacent cavities through the conducting walls. Flow and heat transfer characteristics are studied in detail for various Rayleigh numbers. The convection characteristics in multiple cavities are compared with those in single independent cavity. The thermal interaction between the cavities results in lower temperatures compared with those in independent cavities. While heat is rejected into the adjacent upper cavity through some portion of the conducting wall, heat is received from the adjacent cavity through the remaining portion of the wall. The influence of substrate conductivity on heat exchange between adjacent cavities are examined. Substrate conductivity shows strong effect on temperature distribution. When cooling at both vertical sides is changed to one side cooling, the heat transfer characteristics are changed drastically and many interesting flow features are observed. Effects of cavity aspect ratio is studied and higher heat transfer rates are observed at higher aspect ratios. Correlations for dimensionless temperature maximum and average Nusselt number are presented in terms of Rayleigh number.

Data-resolution based optimal choice of minimum required measurements for image-guided diffuse optical tomography

Image-guided diffuse optical tomography has the advantage of reducing the total number of optical parameters being reconstructed to the number of distinct tissue types identified by the traditional imaging modality, converting the optical image-reconstruction problem from underdetermined in nature to overdetermined. In such cases, the minimum required measurements might be far less compared to those of the traditional diffuse optical imaging. An approach to choose these optimally based on a data-resolution matrix is proposed, and it is shown that such a choice does not compromise the reconstruction performance. (C) 2013 Optical Society of America