152 resultados para depth image


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The efficacy of the multifractal spectrum as a tool for characterizing images has been studied. This spectrum has been computed for digitized images of the nucleus of human cervical cancer cells and it was observed that the entire spectrum is almost fully reproduced for a normal cell while only the right half (q<0) of the spectrum is reproduced for a cancerous cell. Cells in stages in between the two extremes show a shortening of the left half of the spectrum proportional to their condition. The extent of this shortening has been found to be sufficient to permit a classification between three classes of cells at varying distances from a basal cancerous layer-the superficial cells, the intermediate cells and the parabasal cells. This technique may be used for automatic screening of the population while also indicating the stage of malignancy

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Computerized tomography is an imaging technique which produces cross sectional map of an object from its line integrals. Image reconstruction algorithms require collection of line integrals covering the whole measurement range. However, in many practical situations part of projection data is inaccurately measured or not measured at all. In such incomplete projection data situations, conventional image reconstruction algorithms like the convolution back projection algorithm (CBP) and the Fourier reconstruction algorithm, assuming the projection data to be complete, produce degraded images. In this paper, a multiresolution multiscale modeling using the wavelet transform coefficients of projections is proposed for projection completion. The missing coefficients are then predicted based on these models at each scale followed by inverse wavelet transform to obtain the estimated projection data.

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A novel approach for lossless as well as lossy compression of monochrome images using Boolean minimization is proposed. The image is split into bit planes. Each bit plane is divided into windows or blocks of variable size. Each block is transformed into a Boolean switching function in cubical form, treating the pixel values as output of the function. Compression is performed by minimizing these switching functions using ESPRESSO, a cube based two level function minimizer. The minimized cubes are encoded using a code set which satisfies the prefix property. Our technique of lossless compression involves linear prediction as a preprocessing step and has compression ratio comparable to that of JPEG lossless compression technique. Our lossy compression technique involves reducing the number of bit planes as a preprocessing step which incurs minimal loss in the information of the image. The bit planes that remain after preprocessing are compressed using our lossless compression technique based on Boolean minimization. Qualitatively one cannot visually distinguish between the original image and the lossy image and the value of mean square error is kept low. For mean square error value close to that of JPEG lossy compression technique, our method gives better compression ratio. The compression scheme is relatively slower while the decompression time is comparable to that of JPEG.

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The present paper aims at studying the performance characteristics of a subspace based algorithm for source localization in shallow water such as coastal water. Specifically, we study the performance of Multi Image Subspace Algorithm (MISA). Through first-order perturbation analysis and computer simulation it is shown that MISA is unbiased and statistically efficient. Further, we bring out the role of multipaths (or images) in reducing the error in the localization. It is shown that the presence of multipaths is found to improve the range and depth estimates. This may be attributed to the increased curvature of the wavefront caused by interference from many coherent multipaths.

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Novel pyrroloisoquinolines 4 are obtained from 1-methyl-3,4-dihydroisoquinolines 1 by the action of POCl3 and DMF, along with the expected mono- and dialdehydes 2 and 3 respectively and also directly from N-acetyl-2-phenethylamines.

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The jet characteristics and the fluid flow pattern in a continuous slab caster have been studied using a water model. The fluid jet is studied under free fall and submerged discharge conditions. In the latter case, the jet was followed by dye-injection technique and image analyser was used to find out the effect of nozzle parameters on jet-spread angle, jet-discharge angle and the volume entrainment by the jet. All free-fall jets with nozzle port angle zero and upward are found to be spinning. Some of the free-fall jets with downward nozzle-port angle are found to be spinning and rest are smooth. The spinning direction of the jets are found to change with time. The well depth, port diameter and the inner diameter of the nozzle have a clear effect on the free-fall jets with downward port angle. The jet-spread angle is found to be about 17-degrees for smooth jets. The spread angle for spinning jet increases as the nozzle-port angle is increased from downward 25 to upward 15-degrees. The jet-discharge angle is always downward even when the nozzle-discharge ports are angled upward. The extent of volume entrainment by the spinning jet is higher and it increases as the nozzle-port angle is increased from 25 downward to 15-degrees upward.

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Irradiation of 4-aryl-4-alkylhex-5-en-2-ones (e.g. 1a) or 5-aryl-4-alkylhex-5-en-2-ones (e.g. 2a) adsorbed on montmorillonite K-10 in a commercial microwave oven furnishes the multialkylated naphthalenes (e.g. 3).

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In this work, a procedure is presented for the reconstruction of biological organs from image sequences obtained through CT-scan. Although commercial software, which can accomplish this task, are readily available, the procedure presented here needs only free software. The procedure has been applied to reconstruct a liver from the scan data available in literature. 3D biological organs obtained this way can be used for the finite element analysis of biological organs and this has been demonstrated by carrying out an FE analysis on the reconstructed liver.

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This study presents the results of an experimental and analytical comparison of the flexural behavior of a high-strength concrete specimen (no conventional reinforcement) with an average plain concrete cube strength of nearly 65 MPa and containing trough shape steel fibers. Trough shape steel fibers with a volume fraction ranging from 0 to 1.5% and having a constant aspect ratio of 80 have been used in this study. Increased toughness and a more ductile stress-strain response were observed with an increase in fiber content, when the fibers were distributed over the full/partial depth of the beam cross section. Based on the tests, a robust analytical procedure has been proposed to establish the required partial depth to contain fiber-reinforced concrete (FRC) so as to obtain the flexural capacity of a member with FRC over the full depth. It is expected that this procedure will help designers in properly estimating the required partial depth of fibers in composite sections for specific structural applications. Empirical and mechanistic relations have also been proposed in this study to establish the load-deflection behavior of high-strength FRC.

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Depth measures the extent of atom/residue burial within a protein. It correlates with properties such as protein stability, hydrogen exchange rate, protein-protein interaction hot spots, post-translational modification sites and sequence variability. Our server, DEPTH, accurately computes depth and solvent-accessible surface area (SASA) values. We show that depth can be used to predict small molecule ligand binding cavities in proteins. Often, some of the residues lining a ligand binding cavity are both deep and solvent exposed. Using the depth-SASA pair values for a residue, its likelihood to form part of a small molecule binding cavity is estimated. The parameters of the method were calibrated over a training set of 900 high-resolution X-ray crystal structures of single-domain proteins bound to small molecules (molecular weight < 1.5 KDa). The prediction accuracy of DEPTH is comparable to that of other geometry-based prediction methods including LIGSITE, SURFNET and Pocket-Finder (all with Matthew's correlation coefficient of similar to 0.4) over a testing set of 225 single and multi-chain protein structures. Users have the option of tuning several parameters to detect cavities of different sizes, for example, geometrically flat binding sites. The input to the server is a protein 3D structure in PDB format. The users have the option of tuning the values of four parameters associated with the computation of residue depth and the prediction of binding cavities. The computed depths, SASA and binding cavity predictions are displayed in 2D plots and mapped onto 3D representations of the protein structure using Jmol. Links are provided to download the outputs. Our server is useful for all structural analysis based on residue depth and SASA, such as guiding site-directed mutagenesis experiments and small molecule docking exercises, in the context of protein functional annotation and drug discovery.

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A class of I boundary value problems involving propagation of two-dimensional surface water waves, associated with water of uniform finite depth, against a plane vertical wave maker is investigated under the assumption that the surface is covered by a thin sheet of ice. It is assumed that the ice-cover behaves like a thin isotropic elastic plate. Then the problems under consideration lead to those of solving the two-dimensional Laplace equation in a semi-infinite strip, under Neumann boundary conditions on the vertical boundary as well as on one of the horizontal boundaries, representing the bottom of the fluid region, and a condition involving upto fifth order derivatives of the unknown function on the top horizontal ice-covered boundary, along with the two appropriate edge-conditions, at the ice-covered corner, ensuring the uniqueness of the solutions. The mixed boundary value problems are solved completely, by exploiting the regularity property of the Fourier cosine transform.

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In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 sq.km. In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, ordinary kriging and Support Vector Machine (SVM) models have been developed. In ordinary kriging, the knowledge of the semivariogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of Bangalore, where field measurements are not available. A cross validation (Q1 and Q2) analysis is also done for the developed ordinary kriging model. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing e-insensitive loss function has been used to predict the reduced level of rock from a large set of data. A comparison between ordinary kriging and SVM model demonstrates that the SVM is superior to ordinary kriging in predicting rock depth.