231 resultados para Texture image


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Three materials, pure aluminium, Al-4 wt.% Mg, alpha-brass have been chosen to understand the evolution of texture and microstructure during rolling. Pure Al develops a strong copper-type rolling texture and the deformation is entirely slip dominated. In Al-4Mg alloy, texture is copper-type throughout the deformation. The advent of Cu-type shear bands in the later stages of deformation has a negligible effect on the final texture. alpha-brass shows a characteristic brass-type texture from the early stages of rolling. Extensive twinning in the intermediate stages of deformation (epsilon(t) similar to 0.5) causes significant texture reorientation towards alpha-fiber. Beyond 40% reduction, deformation is dominated by Bs-type shear bands, and the banding coincides with the evolution of <111>parallel to ND components. The crystallites within the bands preferentially show <110>parallel to ND components. The absence of the Cu component throughout the deformation process indicates that, for the evolution of brass-type texture, the presence of Cu component is not a necessary condition. The final rolling texture is a synergistic effect of deformation twinning and shear banding.

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This paper describes the evolution of crystallographic texture in three of the most important high strength aluminium alloys, viz., AA2219, AA7075 and AFNOR7020 in the cold rolled and artificially aged condition. Bulk texture results were obtained by plotting pole figures from X-ray diffraction results followed by Orientation Distribution Function (ODF) analysis and micro-textures were measured using EBSD. The results indicate that the deformation texture components Cu, Bs and S, which were also present in the starting materials, strengthen with increase in amount of deformation. On the other hand, recrystallization texture components Goss and Cube weaken. The Bs component is stronger in the deformation texture. This is attributed to the shear banding. In-service applications indicate that the as-processed AFNOR7020 alloy fails more frequently compared to the other high strength Al alloys used in the aerospace industry. Detailed study of deformation texture revealed that strong Brass (Bs) component could be associated to shear banding, which in turn could explain the frequent failures in AFNOR7020 alloy. The alloying elements in this alloy that could possibly influence the stacking fault energy of the material could be accounted for the strong Bs component in the texture.

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Investigations on texture evolution and through-thickness texture heterogeneity during equal channel angular pressing (ECAP) of pure magnesium at 200 degrees C, 150 degrees C and room temperature (RT) was carried out by neutron, high energy synchrotron X-ray and electron back-scatter diffraction. Irrespective of the ECAP temperature, a distinctive basal (B) and pyramidal (C-2) II type of fibers forms. The texture differs in the bottom 1 mm portion, where the B-fiber is shifted similar to 55 degrees due to negative shear attributed to friction. (C) 2015 Elsevier Inc. All rights reserved.

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The present study addresses the evolution of texture and microstructure during annealing in a cryorolled copper. Transition from copper to brass texture during the cryo-rolling has been illustrated. Twinning and interaction between twins and shear bands have been found to play the important role in grain refinement and strengthening. The low temperature vacancy clustering and its effect on the recrystallization have been experimentally demonstrated. Fine scale twinning, and grain refinement have been attributed to the higher yield strength found in the case of samples subjected to cryo-rolling. (C) 2015 Elsevier B.V. All rights reserved.

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This is the first successful attempt to produce Mg-Ce alloys of different texture through different processing routes while keeping the grain size and grain size distribution same. Tensile data shows that contribution of texture to ductility enhancement is primary and that of grain refinement is secondary. The texture resulting from multi-axial forging of extruded billets followed by annealing exhibits the highest ductility (similar to 40%) at room temperature. (C) 2015 Elsevier B.V. All rights reserved.

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In this paper, we propose a super resolution (SR) method for synthetic images using FeatureMatch. Existing state-of-the-art super resolution methods are learning based methods, where a pair of low-resolution and high-resolution dictionary pair are trained, and this trained pair is used to replace patches in low-resolution image with appropriate matching patches from the high-resolution dictionary. In this paper, we show that by using Approximate Nearest Neighbour Fields (ANNF), and a common source image, we can by-pass the learning phase, and use a single image for dictionary. Thus, reducing the dictionary from a collection obtained from hundreds of training images, to a single image. We show that by modifying the latest developments in ANNF computation, to suit super resolution, we can perform much faster and more accurate SR than existing techniques. To establish this claim we will compare our algorithm against various state-of-the-art algorithms, and show that we are able to achieve better and faster reconstruction without any training phase.

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Rapid reconstruction of multidimensional image is crucial for enabling real-time 3D fluorescence imaging. This becomes a key factor for imaging rapidly occurring events in the cellular environment. To facilitate real-time imaging, we have developed a graphics processing unit (GPU) based real-time maximum a-posteriori (MAP) image reconstruction system. The parallel processing capability of GPU device that consists of a large number of tiny processing cores and the adaptability of image reconstruction algorithm to parallel processing (that employ multiple independent computing modules called threads) results in high temporal resolution. Moreover, the proposed quadratic potential based MAP algorithm effectively deconvolves the images as well as suppresses the noise. The multi-node multi-threaded GPU and the Compute Unified Device Architecture (CUDA) efficiently execute the iterative image reconstruction algorithm that is similar to 200-fold faster (for large dataset) when compared to existing CPU based systems. (C) 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

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In big data image/video analytics, we encounter the problem of learning an over-complete dictionary for sparse representation from a large training dataset, which cannot be processed at once because of storage and computational constraints. To tackle the problem of dictionary learning in such scenarios, we propose an algorithm that exploits the inherent clustered structure of the training data and make use of a divide-and-conquer approach. The fundamental idea behind the algorithm is to partition the training dataset into smaller clusters, and learn local dictionaries for each cluster. Subsequently, the local dictionaries are merged to form a global dictionary. Merging is done by solving another dictionary learning problem on the atoms of the locally trained dictionaries. This algorithm is referred to as the split-and-merge algorithm. We show that the proposed algorithm is efficient in its usage of memory and computational complexity, and performs on par with the standard learning strategy, which operates on the entire data at a time. As an application, we consider the problem of image denoising. We present a comparative analysis of our algorithm with the standard learning techniques that use the entire database at a time, in terms of training and denoising performance. We observe that the split-and-merge algorithm results in a remarkable reduction of training time, without significantly affecting the denoising performance.

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Fringe tracking and fringe order assignment have become the central topics of current research in digital photoelasticity. Isotropic points (IPs) appearing in low fringe order zones are often either overlooked or entirely missed in conventional as well as digital photoelasticity. We aim to highlight image processing for characterizing IPs in an isochromatic fringe field. By resorting to a global analytical solution of a circular disk, sensitivity of IPs to small changes in far-field loading on the disk is highlighted. A local theory supplements the global closed-form solutions of three-, four-, and six-point loading configurations of circular disk. The local theoretical concepts developed in this paper are demonstrated through digital image analysis of isochromatics in circular disks subjected to three-and four-point loads. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)

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In spite of intense research on ZnO over the past decade, the detailed investigation about the crystallographic texture of as obtained ZnO thin films/coatings, and its deviation with growth surface is scarce. We report a systematic study about the orientation distribution of nanostructured ZnO thin films fabricated by microwave irradiation with the variation of substrates and surfactants. The nanostructured films comprising of ZnO nanorods are grown on semiconductor substrates such as Si(100), Ge(100)], conducting substrates (ITO-coated glass, Cr coated Si), and polymer coated Si (PMMA/Si) to examine the respective development of crystallographic texture. The ZnO deposited on semiconductor substrates yieldsmixed texture, whereas c-axis oriented ZnO nanostructured films are obtained by conducting substrate, and PMMA coated Si substrates. Among all the surfactants, nanostructured film produced by using the lower molecular weight of polymeric surfactants (polyvinylpyrrolidone) shows a stronger (0002) texture, and that can be tuned to (10 - 10) by increasing the molecular weight of the surfactant. The strongest basal pole is achieved for the ZnO deposited on PMMA coated Si as substrate, and cetyl-trimethyl ammonium bromide as cationic surfactant. The texture analysis is carried out by X-ray pole figure analysis using the Schultz reflection method. (C) 2015 Elsevier B.V. All rights reserved.

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We discuss here a semiconductors assembly comprising of titanium dioxide (TiO2) rods sensitized by cadmium sulfide (CdS) nanocrystals for potential applications in large area electronics on three dimensional (3-D) substrates. Vertically aligned TiO2 rods are grown on a substrate using a 150 degrees C process flow and then sensitized with CdS by SILAR method at room temperature. This structure forms an effective photoconductor as the photo-generated electrons are rapidly removed from the CdS via the TiO2 thereby permitting a hole rich CdS. Current-voltage characteristics are measured and models illustrate space charge limited photo-current as the mechanism of charge transport at moderate voltage bias. The stable assembly and high speed are achieved. The frequency response with a loading of 10 pF and 9 M Omega shows a half power frequency of 100 Hz. (C) 2015 The Electrochemical Society. All rights reserved.

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This paper proposes a denoising algorithm which performs non-local means bilateral filtering. As existing literature suggests, non-local means (NLM) is one of the widely used denoising techniques, but has a critical drawback of smoothing of edges. In order to improve this, we perform fast and efficient NLM using Approximate Nearest Neighbour Fields and improve the edge content in denoising by formulating a joint-bilateral filter. Using the proposed joint bilateral, we are able to denoise smooth regions using the NLM approach and efficient edge reconstruction is obtained from the bilateral filter. Furthermore, to avoid tedious parameter selection, we carry out a noise estimation before performing joint bilateral filtering. The proposed approach is observed to perform well on high noise images.

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Image inpainting is the process of filling the unwanted region in an image marked by the user. It is used for restoring old paintings and photographs, removal of red eyes from pictures, etc. In this paper, we propose an efficient inpainting algorithm which takes care of false edge propagation. We use the classical exemplar based technique to find out the priority term for each patch. To ensure that the edge content of the nearest neighbor patch found by minimizing L-2 distance between patches, we impose an additional constraint that the entropy of the patches be similar. Entropy of the patch acts as a good measure of edge content. Additionally, we fill the image by considering overlapping patches to ensure smoothness in the output. We use structural similarity index as the measure of similarity between ground truth and inpainted image. The results of the proposed approach on a number of examples on real and synthetic images show the effectiveness of our algorithm in removing objects and thin scratches or text written on image. It is also shown that the proposed approach is robust to the shape of the manually selected target. Our results compare favorably to those obtained by existing techniques

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The effect of multiple phases on the evolution of texture during cold rolling and annealing of a copper-iron multilayer, fabricated by accumulative roll bonding, has been studied. The presence of an iron layer affects the deformation texture of the copper layer only at very large strains. On the other hand, a strong effect of copper on iron is observed at both small and large strains. At smaller strains, the larger deformation carried by the copper suppresses the texture development in the iron, whereas, at higher strains, selection of specific orientation relationship at the interface influences the texture of the iron layer. Shear banding and continuous dynamic recrystallization were found to influence the evolution of texture in the copper layer. The influence of large plastic deformation on the recrystallization behavior of copper is demonstrated with the suppression of typical fcc annealing texture components, described as constrained recrystallization. Evolution of typical annealing texture component is suppressed because of the multilayer microstructure. The plane of the interface formed during deformation is determined by a combination of the rolling texture of individual phases, constrained annealing, and the tendency to form a low-energy interface between the two phases during annealing.

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Purpose: A prior image based temporally constrained reconstruction ( PITCR) algorithm was developed for obtaining accurate temperature maps having better volume coverage, and spatial, and temporal resolution than other algorithms for highly undersampled data in magnetic resonance (MR) thermometry. Methods: The proposed PITCR approach is an algorithm that gives weight to the prior image and performs accurate reconstruction in a dynamic imaging environment. The PITCR method is compared with the temporally constrained reconstruction (TCR) algorithm using pork muscle data. Results: The PITCR method provides superior performance compared to the TCR approach with highly undersampled data. The proposed approach is computationally expensive compared to the TCR approach, but this could be overcome by the advantage of reconstructing with fewer measurements. In the case of reconstruction of temperature maps from 16% of fully sampled data, the PITCR approach was 1.57x slower compared to the TCR approach, while the root mean square error using PITCR is 0.784 compared to 2.815 with the TCR scheme. Conclusions: The PITCR approach is able to perform more accurate reconstructions of temperature maps compared to the TCR approach with highly undersampled data in MR guided high intensity focused ultrasound. (C) 2015 American Association of Physicists in Medicine.