911 resultados para Curvature parabola


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Gaussian beam is the asymptotic solution of wave equation concentred at the central ray. The Gaussian beam ray tracing method has many advantages over ray tracing method. Because of the prevalence of multipath and caustics in complex media, Kirchhoff migration usually can not get satisfactory images, but Gaussian beam migration can get better results.The Runge-Kutta method is used to carry out the raytracing, and the wavefront construction method is used to calculate the multipath wavefield. In this thesis, a new method to determine the starting point and initial direction of a new ray is proposed take advantage of the radius of curvature calculated by dynamic ray tracing method.The propagation characters of Gaussian beam in complex media are investigated. When Gaussian beam is used to calculate the Green function, the wave field near the source was decomposed in Gaussian beam in different direction, then the wave field at a point is the superposition of individual Gaussian beams.Migration aperture is the key factor for Kirchhoff migration. In this thesis, the criterion for the choice of optimum aperture is discussed taking advantage of stationary phase analysis. Two equivalent methods are proposed, but the second is more preferable.Gaussian beam migration based on dip scanning and its procedure are developed. Take advantage of the travel time, amplitude, and takeoff angle calculated by Gaussian beam method, the migration is accomplished.Using the proposed migration method, I carry out the numerical calculation of simple theoretical model, Marmousi model and field data, and compare the results with that of Kirchhoff migration. The comparison shows that the new Gaussian beam migration method can get a better result over Kirchhoff migration, with fewer migration noise and clearer image at complex structures.

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In exploration seismology, the geologic target of oil and gas reservoir in complex medium request the high accuracy image of the structure and lithology of the medium. So the study of the prestack image and the elastic inversion of seismic wave in the complex medium come to the leading edge. The seismic response measured at the surface carries two fundamental pieces of information: the propagation effects of the medium and the reflections from the different layer boundaries in the medium. The propagation represent the low-wavenumber component of the medium, it is so-called the trend or macro layering, whereas the reflections represent the high-wavenumber component of the medium, it is called the detailed or fine layering. The result of migration velocity analysis is the resolution of the low-wavenumber component of the medium, but the prestack elastic inversion provided the resolution of the high-wavvenumber component the medium. In the dissertation, the two aspects about the migration velocity estimation and the elastic inversion have been studied.Firstly, any migration velocity analysis methods must include two basic elements: the criterion that tell us how to know whether the model parameters are correct and the updating that tell us how to update the model parameters when they are incorrect, which are effected on the properties and efficiency of the velocity estimation method. In the dissertation, a migration velocity analysis method based on the CFP technology has been presented in which the strategy of the top-down layer stripping approach are adapted to avoid the difficult of the selecting reduce .The proposed method has a advantage that the travel time errors obtained from the DTS panel are defined directly in time which is the difference with the method based on common image gather in which the residual curvature measured in depth should be converted to travel time errors.In the proposed migration velocity analysis method, the four aspects have been improved as follow:? The new parameterization of velocity model is provided in which the boundaries of layers are interpolated with the cubic spline of the control location and the velocity with a layer may change along with lateral position but the value is calculated as a segmented linear function of the velocity of the lateral control points. The proposed parameterization is suitable to updating procedure.? The analytical formulas to represent the travel time errors and the model parameters updates in the t-p domain are derived under local lateral homogeneous. The velocity estimations are iteratively computed as parametric inversion. The zero differential time shift in the DTS panel for each layer show the convergence of the velocity estimation.? The method of building initial model using the priori information is provided to improve the efficiency of velocity analysis. In the proposed method, Picking interesting events in the stacked section to define the boundaries of the layers and the results of conventional velocity analysis are used to define the velocity value of the layers? An interactive integrate software environment with the migration velocity analysis and prestack migration is built.The proposed method is firstly used to the synthetic data. The results of velocity estimation show both properties and efficiency of the velocity estimation are very good.The proposed method is also used to the field data which is the marine data set. In this example, the prestack and poststack depth migration of the data are completed using the different velocity models built with different method. The comparison between them shows that the model from the proposed method is better and improves obviously the quality of migration.In terms of the theoretical method of expressing a multi-variable function by products of single-variable functions which is suggested by Song Jian (2001), the separable expression of one-way wave operator has been studied. A optimization approximation with separable expression of the one-way wave operator is presented which easily deal with the lateral change of velocity in space and wave number domain respectively and has good approach accuracy. A new prestack depth migration algorithm based on the optimization approximation separable expression is developed and used to testing the results of velocity estimation.Secondly, according to the theory of the seismic wave reflection and transmission, the change of the amplitude via the incident angle is related to the elasticity of medium in the subsurface two-side. In the conventional inversion with poststack datum, only the information of the reflection operator at the zero incident angles can be used. If the more robust resolutions are requested, the amplitudes of all incident angles should be used.A natural separable expression of the reflection/transmission operator is represented, which is the sum of the products of two group functions. One group function vary with phase space whereas other group function is related to elastic parameters of the medium and geological structure.By employing the natural separable expression of the reflection/transmission operator, the method of seismic wave modeling with the one-way wave equation is developed to model the primary reflected waves, it is adapt to a certain extent heterogeneous media and confirms the accuracy of AVA of the reflections when the incident angle is less than 45'. The computational efficiency of the scheme is greatly high.The natural separable expression of the reflection/transmission operator is also used to construct prestack elastic inversion algorithm. Being different from the AVO analysis and inversion in which the angle gathers formed during the prstack migration are used, the proposed algorithm construct a linear equations during the prestack migration by the separable expression of the reflection/transmission operator. The unknowns of the linear equations are related to the elasticity of the medium, so the resolutions of them provided the elastic information of the medium.The proposed method of inversion is the same as AVO inversion in , the difference between them is only the method processing the amplitude via the incident angle and computational domain.

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Structure from motion often refers to the computation of 3D structure from a matched sequence of images. However, a depth map of a surface is difficult to compute and may not be a good representation for storage and recognition. Given matched images, I will first show that the sign of the normal curvature in a given direction at a given point in the image can be computed from a simple difference of slopes of line-segments in one image. Using this result, local surface patches can be classified as convex, concave, parabolic (cylindrical), hyperbolic (saddle point) or planar. At the same time the translational component of the optical flow is obtained, from which the focus of expansion can be computed.

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The interpretation and recognition of noisy contours, such as silhouettes, have proven to be difficult. One obstacle to the solution of these problems has been the lack of a robust representation for contours. The contour is represented by a set of pairwise tangent circular arcs. The advantage of such an approach is that mathematical properties such as orientation and curvature are explicityly represented. We introduce a smoothing criterion for the contour tht optimizes the tradeoff between the complexity of the contour and proximity of the data points. The complexity measure is the number of extrema of curvature present in the contour. The smoothing criterion leads us to a true scale-space for contours. We describe the computation of the contour representation as well as the computation of relevant properties of the contour. We consider the potential application of the representation, the smoothing paradigm, and the scale-space to contour interpretation and recognition.

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This work addresses two related questions. The first question is what joint time-frequency energy representations are most appropriate for auditory signals, in particular, for speech signals in sonorant regions. The quadratic transforms of the signal are examined, a large class that includes, for example, the spectrograms and the Wigner distribution. Quasi-stationarity is not assumed, since this would neglect dynamic regions. A set of desired properties is proposed for the representation: (1) shift-invariance, (2) positivity, (3) superposition, (4) locality, and (5) smoothness. Several relations among these properties are proved: shift-invariance and positivity imply the transform is a superposition of spectrograms; positivity and superposition are equivalent conditions when the transform is real; positivity limits the simultaneous time and frequency resolution (locality) possible for the transform, defining an uncertainty relation for joint time-frequency energy representations; and locality and smoothness tradeoff by the 2-D generalization of the classical uncertainty relation. The transform that best meets these criteria is derived, which consists of two-dimensionally smoothed Wigner distributions with (possibly oriented) 2-D guassian kernels. These transforms are then related to time-frequency filtering, a method for estimating the time-varying 'transfer function' of the vocal tract, which is somewhat analogous to ceptstral filtering generalized to the time-varying case. Natural speech examples are provided. The second question addressed is how to obtain a rich, symbolic description of the phonetically relevant features in these time-frequency energy surfaces, the so-called schematic spectrogram. Time-frequency ridges, the 2-D analog of spectral peaks, are one feature that is proposed. If non-oriented kernels are used for the energy representation, then the ridge tops can be identified, with zero-crossings in the inner product of the gradient vector and the direction of greatest downward curvature. If oriented kernels are used, the method can be generalized to give better orientation selectivity (e.g., at intersecting ridges) at the cost of poorer time-frequency locality. Many speech examples are given showing the performance for some traditionally difficult cases: semi-vowels and glides, nasalized vowels, consonant-vowel transitions, female speech, and imperfect transmission channels.

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The problem of using image contours to infer the shapes and orientations of surfaces is treated as a problem of statistical estimation. The basis for solving this problem lies in an understanding of the geometry of contour formation, coupled with simple statistical models of the contour generating process. This approach is first applied to the special case of surfaces known to be planar. The distortion of contour shape imposed by projection is treated as a signal to be estimated, and variations of non-projective origin are treated as noise. The resulting method is then extended to the estimation of curved surfaces, and applied successfully to natural images. Next, the geometric treatment is further extended by relating countour curvature to surface curvature, using cast shadows as a model for contour generation. This geometric relation, combined with a statistical model, provides a measure of goodness-of-fit between a surface and an image contour. The goodness-of-fit measure is applied to the problem of establishing registration between an image and a surface model. Finally, the statistical estimation strategy is experimentally compared to human perception of orientation: human observers' judgements of tilt correspond closely to the estimates produced by the planar strategy.

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Redundant sensors are needed on a mobile robot so that the accuracy with which it perceives its surroundings can be increased. Sonar and infrared sensors are used here in tandem, each compensating for deficiencies in the other. The robot combines the data from both sensors to build a representation which is more accurate than if either sensor were used alone. Another representation, the curvature primal sketch, is extracted from this perceived workspace and is used as the input to two path planning programs: one based on configuration space and one based on a generalized cone formulation of free space.

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This report explores the relation between image intensity and object shape. It is shown that image intensity is related to surface orientation and that a variation in image intensity is related to surface curvature. Computational methods are developed which use the measured intensity variation across surfaces of smooth objects to determine surface orientation. In general, surface orientation is not determined locally by the intensity value recorded at each image point. Tools are needed to explore the problem of determining surface orientation from image intensity. The notion of gradient space , popularized by Huffman and Mackworth, is used to represent surface orientation. The notion of a reflectance map, originated by Horn, is used to represent the relation between surface orientation image intensity. The image Hessian is defined and used to represent surface curvature. Properties of surface curvature are expressed as constraints on possible surface orientations corresponding to a given image point. Methods are presented which embed assumptions about surface curvature in algorithms for determining surface orientation from the intensities recorded in a single view. If additional images of the same object are obtained by varying the direction of incident illumination, then surface orientation is determined locally by the intensity values recorded at each image point. This fact is exploited in a new technique called photometric stereo. The visual inspection of surface defects in metal castings is considered. Two casting applications are discussed. The first is the precision investment casting of turbine blades and vanes for aircraft jet engines. In this application, grain size is an important process variable. The existing industry standard for estimating the average grain size of metals is implemented and demonstrated on a sample turbine vane. Grain size can be computed form the measurements obtained in an image, once the foreshortening effects of surface curvature are accounted for. The second is the green sand mold casting of shuttle eyes for textile looms. Here, physical constraints inherent to the casting process translate into these constraints, it is necessary to interpret features of intensity as features of object shape. Both applications demonstrate that successful visual inspection requires the ability to interpret observed changes in intensity in the context of surface topography. The theoretical tools developed in this report provide a framework for this interpretation.

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RESUMO: Com o objetivo de avaliar o desempenho agronômico de genótipos de girassol nas condições edafoclimáticas do primeiro semestre de 2015 na Chapada do Araripe, instalou-se um experimento na Estação Experimental do Instituto Agronômico de Pernambuco (IPA), no município de Araripina, Estado de Pernambuco. O delineamento foi o de blocos ao acaso, com quatro repetições e 13 tratamentos, correspondendo aos genótipos de girassol: M734, NTC 90, BRS G43, BRS G44, BRS G45, BRS G46, SYN 065, HLA 2013, HLA 2014, HLA 2015, HLA 2016, HLA 2017 e SYN 045. Avaliaram-se as seguintes características: sobrevivência final, floração inicial, maturação fisiológica, altura média do capítulo, peso de 1000 aquênios, diâmetro médio dos capítulos, produção final de aquênios, curvatura do capítulo e plantas acamadas, quebradas e atacadas por pássaros. Os genótipos apresentaram diferenças morfoagronômicas quando cultivados no primeiro semestre em condições edafoclimáticas da região do Araripe, com exceção da variável sobrevivência. O genótipo NTC 90 alcançou o maior peso de aquênios. Todos os genótipos, exceto HLA 2015, apresentaram elevado rendimento de grãos. Os caracteres plantas acamadas, quebradas, atacadas por pássaros ou a curvatura do capítulo não foram relacionadas às diferentes cultivares. ABSTRACT: The study aimed to evaluate the agronomic performance of different sunflower genotypes in edaphoclimatic conditions of Araripe region in the first semester of 2015. The experiment was established at the Experimental Station of Instituto Agronômico de Pernambuco (IPA), Araripina, Pernambuco, Brazil. Experimental design was a randomized blocks with thirteen treatments, corresponding to the sunflower genotypes: M734, NTC 90, BRS G43, BRS G44, BRS G45, BRS G46, SYN 065, HLA 2013, HLA 2014, HLA 2015, HLA 2016, HLA 2017 e SYN 045, with four replicates. The following characteristics were evaluated: final survival, early flowering, physiological maturity, average plant height, weight of 1,000 seeds, average flower diameter, final seed production, flower head curvature, lodged, broken and damaged by birds plants. The genotypes showed morphoagronomic differences when grown in the first semester of 2015 on edaphoclimatic conditions of the Araripe region, except for the variable survival. The NTC 90 genotype achieved the highest weight of head flower. All genotypes, except HLA 2015 showed high grain yield. The characters lodged, broken and damaged plants by birds or curvature of the head flower were not related to the different cultivars.

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RESUMO: O objetivo deste trabalho foi avaliar características agronômicos durante o desenvolvimento de híbridos de girassol cultivados na região de Campo Novo do Parecis - MT. O ensaio foi instalado e conduzido,entre os meses de fevereiro ejunho de 2015, na área experimental do setor de produção do Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso - IFMT Campus Campo Novo do Parecis - MT, cujas coordenadas geográficas são latitude S 13°40'31" longitude O 57°53'31" e altitude média de 574 m. O solo predominante é Latossolo Vermelho distrófico típico. O delineamento experimental foi em blocos casualizados com 13 tratamentos (híbridos) e 4 repetições, totalizando um total de 52 parcelas. Foram avaliadas as seguintes características agronômicas do girassol: dias para o florescimento inicial, dias para a maturação fisiológica, altura de planta, curvatura do caule, número de plantas acamadas, número de plantas quebradas e produtividade de aquênios. Os dados foram submetidos à análise de variância e ao teste de média Scott-Knott (p<0,05). O híbrido BRS G44 apresentou híbrido BRS G44 apresentou bom rendimento, ciclo precoce e porte baixo, nas condições de segunda safra de verão em Campo Novo do Parecis (MT) . Assim, este híbrido se torna boa opção para o cultivo de girassol na região. ABSTRACT: The objective of this study was to evaluate agronomic characteristics for the development of sunflower hybrids grown in the region of Campo Novo do Parecis - MT. The experiment was carried out and conducted between the months of February to June 2015 in the experimental area of the production sector of the Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso, - IFMT, Campo Novo do Parecis - MT (latitude S 13°40'31" longitude W 57°53'31" and average altitude of 574 m). The predominant soil is Typic Tropudox. The experimental design was randomized blocks with 13 treatments (hybrids) and four repetitions, resulting in 52 plots. The sunflower agronomic traits evaluated were: days to initial flowering, days to physiological maturity, plant height, stem curvature, number of lodged plants, number of broken plants and achenes productivity. Data were subjected to analysis of variance and average test Scott-Knott (p<0.05). The hybrid BRS G44 showed good yield, early maturity and low height in second summer crop conditions in Campo Novo do Parecis (MT). Thus, this hybrid is a good option for sunflower cultivation in the region.

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R. Marti, R. Zwiggelaar, C.M.E. Rubin, 'Automatic point correspondence and registration based on linear structures', International Journal of Pattern Recognition and Artificial Intelligence 16 (3), 331-340 (2002)

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Douglas, Robert; Cullen, M.J.P.; Roulston, I.; Sewell, M.J., (2005) 'Generalized semi-geostrophic theory on a sphere', Journal of Fluid Mechanics 531 pp.123-157 RAE2008

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Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Medicina Dentária

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A novel method that combines shape-based object recognition and image segmentation is proposed for shape retrieval from images. Given a shape prior represented in a multi-scale curvature form, the proposed method identifies the target objects in images by grouping oversegmented image regions. The problem is formulated in a unified probabilistic framework and solved by a stochastic Markov Chain Monte Carlo (MCMC) mechanism. By this means, object segmentation and recognition are accomplished simultaneously. Within each sampling move during the simulation process,probabilistic region grouping operations are influenced by both the image information and the shape similarity constraint. The latter constraint is measured by a partial shape matching process. A generalized parallel algorithm by Barbu and Zhu,combined with a large sampling jump and other implementation improvements, greatly speeds up the overall stochastic process. The proposed method supports the segmentation and recognition of multiple occluded objects in images. Experimental results are provided for both synthetic and real images.

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Much sensory-motor behavior develops through imitation, as during the learning of handwriting by children. Such complex sequential acts are broken down into distinct motor control synergies, or muscle groups, whose activities overlap in time to generate continuous, curved movements that obey an intense relation between curvature and speed. The Adaptive Vector Integration to Endpoint (AVITEWRITE) model of Grossberg and Paine (2000) proposed how such complex movements may be learned through attentive imitation. The model suggest how frontal, parietal, and motor cortical mechanisms, such as difference vector encoding, under volitional control from the basal ganglia, interact with adaptively-timed, predictive cerebellar learning during movement imitation and predictive performance. Key psycophysical and neural data about learning to make curved movements were simulated, including a decrease in writing time as learning progresses; generation of unimodal, bell-shaped velocity profiles for each movement synergy; size scaling with isochrony, and speed scaling with preservation of the letter shape and the shapes of the velocity profiles; an inverse relation between curvature and tangential velocity; and a Two-Thirds Power Law relation between angular velocity and curvature. However, the model learned from letter trajectories of only one subject, and only qualitative kinematic comparisons were made with previously published human data. The present work describes a quantitative test of AVITEWRITE through direct comparison of a corpus of human handwriting data with the model's performance when it learns by tracing human trajectories. The results show that model performance was variable across subjects, with an average correlation between the model and human data of 89+/-10%. The present data from simulations using the AVITEWRITE model highlight some of its strengths while focusing attention on areas, such as novel shape learning in children, where all models of handwriting and learning of other complex sensory-motor skills would benefit from further research.