65 resultados para Shape-from-texture


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The stratigraphic subdivision and correlation of dune deposits is difficult, especially when age datings are not available. A better understanding of the controls on texture and composition of eolian sands is necessary to interpret ancient eolian sediments. The Imbituba-Jaguaruna coastal zone (Southern Brazil, 28 degrees-29 degrees S) stands out due to its four well-preserved Late Pleistocene (eolian generation 1) to Holocene eolian units (eolian generations 2, 3, and 4). In this study, we evaluate the grain-size and heavy-mineral characteristics of the Imbituba-Jaguartma eolian units through statistical analysis of hundreds of sediment samples. Grain-size parameters and heavy-mineral content allow us to distinguish the Pleistocene from the Holocene units. The grain size displays a pattern of fining and better sorting from generation 1 (older) to 4 (younger), whereas the content of mechanically stable (dense and hard) heavy minerals decreases from eolian generation 1 to 4. The variation in grain size and heavy-mineral content records shifts in the origin and balance (input versus output) of eolian sediment supply attributable mainly to relative sea-level changes. Dunefields submitted to relative sea-level lowstand conditions (eolian generation 1) are characterized by lower accumulation rates and intense post-depositional dissection by fluvial incision. Low accumulation rates favor deflation in the eolian system, which promotes concentration of denser and stable heavy minerals (increase of ZTR index) as well as coarsening of eolian sands. Dissection involves the selective removal of finer sediments and less dense heavy minerals to the coastal source area. Under a high rate of relative sea-level rise and transgression (eolian generation 2), coastal erosion prevents deflation through high input of sediments to the coastal eolian source. This condition favors dunefield growth. Coastal erosion feeds sand from local sources to the eolian system. including sands from previous dunefields (eolian generation 1) and from drowned incised valleys. Therefore, dunefields corresponding to transgressive phases inherit the grain-size and heavy-mineral characteristics of previous dunefields, leading to selective enrichment of finer sands and lighter minerals. Eolian generations 3 and 4 developed during a regressive-progradational phase (Holocene relative sea level highstand). The high rate of sediment supply during the highstand phase prevents deflation. The lack of coastal erosion favors sediment supply from distal sources (fluvial sediments rich in unstable heavy minerals). Thus, dunefields of transgressive and highstand systems tracts may be distinguished from dunefields of the lowstand systems tract through high rates of accumulation (low deflation) in the former. The sediment source of the transgressive dunefields (high input of previously deposited coastal sands) differs from that of the highstand dunefields (high input of fluvial distal sands). Based on this case study, we propose a general framework for the relation between relative sea level, sediment supply and the texture and mineralogy of eolian sediments deposited in siliciclastic wet coastal zones similar to the Imbituba-Jaguaruna coast (C) 2009 Elsevier B.V. All rights reserved.

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In this paper, we present a 3D face photography system based on a facial expression training dataset, composed of both facial range images (3D geometry) and facial texture (2D photography). The proposed system allows one to obtain a 3D geometry representation of a given face provided as a 2D photography, which undergoes a series of transformations through the texture and geometry spaces estimated. In the training phase of the system, the facial landmarks are obtained by an active shape model (ASM) extracted from the 2D gray-level photography. Principal components analysis (PCA) is then used to represent the face dataset, thus defining an orthonormal basis of texture and another of geometry. In the reconstruction phase, an input is given by a face image to which the ASM is matched. The extracted facial landmarks and the face image are fed to the PCA basis transform, and a 3D version of the 2D input image is built. Experimental tests using a new dataset of 70 facial expressions belonging to ten subjects as training set show rapid reconstructed 3D faces which maintain spatial coherence similar to the human perception, thus corroborating the efficiency and the applicability of the proposed system.

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This paper presents a new framework for generating triangular meshes from textured color images. The proposed framework combines a texture classification technique, called W-operator, with Imesh, a method originally conceived to generate simplicial meshes from gray scale images. An extension of W-operators to handle textured color images is proposed, which employs a combination of RGB and HSV channels and Sequential Floating Forward Search guided by mean conditional entropy criterion to extract features from the training data. The W-operator is built into the local error estimation used by Imesh to choose the mesh vertices. Furthermore, the W-operator also enables to assign a label to the triangles during the mesh construction, thus allowing to obtain a segmented mesh at the end of the process. The presented results show that the combination of W-operators with Imesh gives rise to a texture classification-based triangle mesh generation framework that outperforms pixel based methods. Crown Copyright (C) 2009 Published by Elsevier Inc. All rights reserved.

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This work describes a novel methodology for automatic contour extraction from 2D images of 3D neurons (e.g. camera lucida images and other types of 2D microscopy). Most contour-based shape analysis methods cannot be used to characterize such cells because of overlaps between neuronal processes. The proposed framework is specifically aimed at the problem of contour following even in presence of multiple overlaps. First, the input image is preprocessed in order to obtain an 8-connected skeleton with one-pixel-wide branches, as well as a set of critical regions (i.e., bifurcations and crossings). Next, for each subtree, the tracking stage iteratively labels all valid pixel of branches, tip to a critical region, where it determines the suitable direction to proceed. Finally, the labeled skeleton segments are followed in order to yield the parametric contour of the neuronal shape under analysis. The reported system was successfully tested with respect to several images and the results from a set of three neuron images are presented here, each pertaining to a different class, i.e. alpha, delta and epsilon ganglion cells, containing a total of 34 crossings. The algorithms successfully got across all these overlaps. The method has also been found to exhibit robustness even for images with close parallel segments. The proposed method is robust and may be implemented in an efficient manner. The introduction of this approach should pave the way for more systematic application of contour-based shape analysis methods in neuronal morphology. (C) 2008 Elsevier B.V. All rights reserved.

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The synthesis and self-assembly of tetragonal phase-containing L1(0)-Fe(55)Pt(45) nanorods with high coercive field is described. The experimental procedure resulted in a tetragonal/cubic phase ratio close to 1:1 for the as-synthesized nanoparticles. Using different surfactant/solvent proportions in the process allowed control of particle morphology from nanospheres to nanowires. Monodisperse nanorods with lengths of 60 +/- 5 nm and diameters of 2-3 nm were self-assembled in a perpendicular oriented array onto a substrate surface using hexadecylamine as organic spacer. Magnetic alignment and properties assigned, respectively, to the shape anisotropy and the tetragonal phase suggest that the self-assembled materials are a strong candidate to solve the problem of random magnetic alignment observed in FePt nanospheres leading to applications in ultrahigh magnetic recording (UHMR) systems capable of achieving a performance of the order of terabits/in(2).