Evaluation of 2D image reconstruction using fan-beam FBP algorithm with no backprojection weight from WLP completed truncated projection data

This paper presents the image reconstruction using the fan-beam filtered backprojection (FBP) algorithm with no backprojection weight from windowed linear prediction (WLP) completed truncated projection data. The image reconstruction from truncated projections aims to reconstruct the object accurately from the available limited projection data. Due to the incomplete projection data, the reconstructed image contains truncation artifacts which extends into the region of interest (ROI) making the reconstructed image unsuitable for further use. Data completion techniques have been shown to be effective in such situations. We use windowed linear prediction technique for projection completion and then use the fan-beam FBP algorithm with no backprojection weight for the 2-D image reconstruction. We evaluate the quality of the reconstructed image using fan-beam FBP algorithm with no backprojection weight after WLP completion.

Materials, Processing, and Testing of Flexible Image Sensor Arrays

Editors' note:Flexible, large-area display and sensor arrays are finding growing applications in multimedia and future smart homes. This article first analyzes and compares current flexible devices, then discusses the implementation, requirements, and testing of flexible sensor arrays.—Jiun-Lang Huang (National Taiwan University) and Kwang-Ting (Tim) Cheng (University of California, Santa Barbara)

Multi-objective optimization of satellite image registration using discrete Pparticle swarm optimisation

A new multi-sensor image registration technique is proposed based on detecting the feature corner points using modified Harris Corner Detector (HDC). These feature points are matched using multi-objective optimization (distance condition and angle criterion) based on Discrete Particle Swarm Optimization (DPSO). This optimization process is more efficient as it considers both the distance and angle criteria to incorporate multi-objective switching in the fitness function. This optimization process helps in picking up three corresponding corner points detected in the sensed and base image and thereby using the affine transformation, the sensed image is aligned with the base image. Further, the results show that the new approach can provide a new dimension in solving multi-sensor image registration problems. From the obtained results, the performance of image registration is evaluated and is concluded that the proposed approach is efficient.

Studies and Evaluation of EIT Image Reconstruction in EIDORS with Simulated Boundary Data

Simulated boundary potential data for Electrical Impedance Tomography (EIT) are generated by a MATLAB based EIT data generator and the resistivity reconstruction is evaluated with Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software (EIDORS). Circular domains containing subdomains as inhomogeneity are defined in MATLAB-based EIT data generator and the boundary data are calculated by a constant current simulation with opposite current injection (OCI) method. The resistivity images reconstructed for different boundary data sets and images are analyzed with image parameters to evaluate the reconstruction.

Microscopic origin of the chirality driven morphologies of the amphiphilic monolayers and bilayers

It is widely known that the compressed monolayers and bilayers of chiral lipids or fatty acids form helical morphologies, while the corresponding racemic modification gives only flat platelets without twist. No molecular explanation of this phenomenon is yet available, although subtle interactions at the chiral centers have often been proposed as the driving force behind the morphology of the aggregate to form a particular shape. In the present study, the morphologies of the chiral amphiphilic assemblies have been predicted on the basis of an effective pair potential between the molecules, which depends on the relative sizes of the groups attached to the chiral centers, the orientation of the amphiphilic molecules and also on the distance between them. It is shown that fur a pair of same kind of enantiomers, the minimum energy conformation favours a twist angle between them. This twist between the neighbouring molecules gives rise to the helicity of the aggregate. The present theory also shows from the molecular considerations that for a pair of mirror-image isomers (i.e. the racemic modification) the minimum energy conformation corresponds to the zero angle between the molecules, thus giving rise to flat platelets as observed in experiments. Another fascinating aspect of such chirality driven helical structures is that the sense (or the handedness) of the helix is highly specific about the chirality of the monomer concerned. The molecular theory shows, for the first time, that the sense of the helical structures in many cases is determined by the sizes of the groups attached to the chiral centers and the effective potential between them. The predicted senses of the helical structures are in complete agreement with the experimental results.

VLSI Implementation of Spatial prediction Based Image Compression Scheme

We propose the design and implementation of hardware architecture for spatial prediction based image compression scheme, which consists of prediction phase and quantization phase. In prediction phase, the hierarchical tree structure obtained from the test image is used to predict every central pixel of an image by its four neighboring pixels. The prediction scheme generates an error image, to which the wavelet/sub-band coding algorithm can be applied to obtain efficient compression. The software model is tested for its performance in terms of entropy, standard deviation. The memory and silicon area constraints play a vital role in the realization of the hardware for hand-held devices. The hardware architecture is constructed for the proposed scheme, which involves the aspects of parallelism in instructions and data. The processor consists of pipelined functional units to obtain the maximum throughput and higher speed of operation. The hardware model is analyzed for performance in terms throughput, speed and power. The results of hardware model indicate that the proposed architecture is suitable for power constrained implementations with higher data rate

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.

Integration of speckle de-noising and image segmentation using synthetic aperture radar image for flood extent extraction

Flood is one of the detrimental hydro-meteorological threats to mankind. This compels very efficient flood assessment models. In this paper, we propose remote sensing based flood assessment using Synthetic Aperture Radar (SAR) image because of its imperviousness to unfavourable weather conditions. However, they suffer from the speckle noise. Hence, the processing of SAR image is applied in two stages: speckle removal filters and image segmentation methods for flood mapping. The speckle noise has been reduced with the help of Lee, Frost and Gamma MAP filters. A performance comparison of these speckle removal filters is presented. From the results obtained, we deduce that the Gamma MAP is reliable. The selected Gamma MAP filtered image is segmented using Gray Level Co-occurrence Matrix (GLCM) and Mean Shift Segmentation (MSS). The GLCM is a texture analysis method that separates the image pixels into water and non-water groups based on their spectral feature whereas MSS is a gradient ascent method, here segmentation is carried out using spectral and spatial information. As test case, Kosi river flood is considered in our study. From the segmentation result of both these methods are comprehensively analysed and concluded that the MSS is efficient for flood mapping.

Variation at Diabetes- and Obesity-Associated Loci May Mirror Neutral Patterns of Human Population Diversity and Diabetes Prevalence in India

South Asian populations harbor a high degree of genetic diversity, due in part to demographic history. Two studies on genome-wide variation in Indian populations have shown that most Indian populations show varying degrees of admixture between ancestral north Indian and ancestral south Indian components. As a result of this structure, genetic variation in India appears to follow a geographic cline. Similarly, Indian populations seem to show detectable differences in diabetes and obesity prevalence between different geographic regions of the country. We tested the hypothesis that genetic variation at diabetes-and obesity-associated loci may be potentially related to different genetic ancestries. We genotyped 2977 individuals from 61 populations across India for 18 SNPs in genes implicated in T2D and obesity. We examined patterns of variation in allele frequency across different geographical gradients and considered state of origin and language affiliation. Our results show that most of the 18 SNPs show no significant correlation with latitude, the geographic cline reported in previous studies, or by language family. Exceptions include KCNQ1 with latitude and THADA and JAK1 with language, which suggests that genetic variation at previously ascertained diabetes-associated loci may only partly mirror geographic patterns of genome-wide diversity in Indian populations.

Estimation of gear tooth deflection by the finite element method

The finite element method (FEM) is used to determine for pitch-point, mid-point and tip loading, the deflection curve of a Image 1 diamentral pitch (DP) standard spur gear tooth corresponding to number of teeth of 14, 21, 26 and 34. In all these cases the deflection of the gear tooth at the point of loading obtained by FEM is in good agreement with the experimental value. The contraflexure in the deflection curve at the point of loading observed experimentally in the cases of pitch-point and mid-point loading, is predicted correctly by the FEM analysis.

A conformational approach to the study of the dynamics of enzyme inhibition: studies on thermolysin

The preferred conformations of β-phenylpropionyl-Image -phenylalanine (β-PPP) and N-carbobenzoxy-L-phenylalanine (Cbz-Phe), two inhibitors of thermolysin, have been determined by computing potential energy using empirial potential energy functions. Of the 15 to 20 conformations that are favoured for each of these inhibitors only a few have the right conformation to reach the active site of the enzyme. The conformer of β-PPP that initiates binding with the enzyme is different from the bound one, while for Cbz-Phe the bound and initiating conformers are quite similar. Thus, β-PPP favours the ‘induced fit’ model while Cbz-Phe follows the ‘lock and key’ model of binding. The inhibitors differ in their alignment at the active site.

Modes of deformation in aluminium rings subjected to static axial compression

Aluminium rings of varying Image Image diameter ratios machined from extruded solid bars, were subjected to static axial compression. Etched diametral planes of deformed cylinders revealed the existence of shear bands, the configuration of which were found to change with initial specimen geometry and deformation.

Preparation and x-ray characterization of four new crystal forms of Jacalin, a lectin from Artocarpus integrifolia

Four new crystal forms of the anti-T lectin from jackfruit (Artocarpus integrifolia) have been prepared and characterized. Three of them, two monoclinic (P21, A = 59·4 Å, B = 83·3 Å, C = 63·5 Å, β = 107·7°; C2, A = 106·1,Å, B = 53·9 Å, C = 128·0 Å, β = 95·0 Å) and one orthorhombic (C2221, A = 98·1 Å, B = 67·3 Å, C = 95·1 Å) were grown with 2-methylpentan-2,4-diol (MPD) as the precipitant while the fourth, an hexagonal from (P6122, A = b = 129·6 Å, C = 157·9 Å), was obtained in the presence of methyl-ga-Image -galactopyranoside with polyethylene glycol 4000 as the precipitant. The reported relative molecular mass (Mr) of the lectin was found to be inconsistent with the solvent content of the crystals estimated using measured densities. The Mr was redetermined using size-exclusion chromatography in the presence of methyl-α-Image -galactopyranoside and Ferguson-plot analysis of mobilities in polyacrylamide gel electrophoresis. The redetermined Mr (66,000) is consistent with the measured crystal densities. The orthorhombic and the hexagonal forms, which have one half molecule and one molecule, respectively, in the asymmetric unit, are suitable for high-resolution X-ray analysis.

Edge-based connected component approach for skew correction of complex document images

Skew correction of complex document images is a difficult task. We propose an edge-based connected component approach for robust skew correction of documents with complex layout and content. The algorithm essentially consists of two steps - an 'initialization' step to determine the image orientation from the centroids of the connected components and a 'search' step to find the actual skew of the image. During initialization, we choose two different sets of points regularly spaced across the the image, one from the left to right and the other from top to bottom. The image orientation is determined from the slope between the two succesive nearest neighbors of each of the points in the chosen set. The search step finds succesive nearest neighbors that satisfy the parameters obtained in the initialization step. The final skew is determined from the slopes obtained in the 'search' step. Unlike other connected component based methods, the proposed method does not require any binarization step that generally precedes connected component analysis. The method works well for scanned documents with complex layout of any skew with a precision of 0.5 degrees.

Localization of handwritten text in documents using moment invariants and Delaunay triangulation

This paper describes an approach based on Zernike moments and Delaunay triangulation for localization of hand-written text in machine printed text documents. The Zernike moments of the image are first evaluated and we classify the text as hand-written using the nearest neighbor classifier. These features are independent of size, slant, orientation, translation and other variations in handwritten text. We then use Delaunay triangulation to reclassify the misclassified text regions. When imposing Delaunay triangulation on the centroid points of the connected components, we extract features based on the triangles and reclassify the text. We remove the noise components in the document as part of the preprocessing step so this method works well on noisy documents. The success rate of the method is found to be 86%. Also for specific hand-written elements such as signatures or similar text the accuracy is found to be even higher at 93%.