Optimal orientation estimators for detection of cylindrical objects

International audienceThis paper introduces low level operators in the context of detecting cylindrical axis in 3 D images. Knowing the axis of a cylinder is particularly useful since cylinder location, length and curvature derive from this knowledge. This paper introduces a new gradient-based optimal operator dedicated to accurate estimation of the direction toward the axis. The operator relies on Finite Impulse Response filters. The approach is presented first in a 2-D context, thus providing optimal gradient masks for locating the center of circular objects. Then, a 3-D extension is provided, allowing the exact estimation of the orientation toward the axis of cylindrical objects when this axis coincides with one of the mask reference axes. Applied to more general cylinders and to noisy data, the operator still provides accurate estimation and outperforms classical gradient operators

Modelling Chemical Vapour Infiltration in C/C composites: numerical tools based on µ-CT images

ISBN 978-3-00-032049-1International audienceIn the production of high-quality Ceramic-Matrix Composites, matrix preparation is often made by Chemical Vapor Infiltration (CVI), a process which involves many phenomena such as gas transport, chemical reactions, and structural evolution of the preform. Control and optimization of this high-tech process are demanding for modeling tools.In this context, a numerical simulation of CVI in complex 3D images, acquired e.g. by X-ray Computerized Microtomography, has been developed. The approach addresses the two length scales which are inherent to a composite with woven textile reinforcement (i.e. inter- and intra-bundle), with two numerical tools.The small-scale program allows direct simulation of CVI in small intra-bundle pores. Effective laws for porosity, surface and transport properties as infiltration proceeds are produced by averaging. They are an input for the next modeling step.The second code is a large-scale solver which accounts for the locally heterogeneous and anisotropic character of the pore space. Simulation of the infiltration of a whole composite material part is possible with this program.Validation of these tools on test cases, as well as some examples on actual materials, are shown and discussed

An annotated image dataset of vegetable crops at an early stage of growth for proximal sensing applications

This article introduces a dataset of 2 801 images of vegetable crops. Maize (Zea mays), bean (Phaseolus vulgaris) and leek (Allium ampeloprasum) crops at an early stage of development (between 2 and 5 weeks from seeding of transplanting) are supported. Two kinds of annotations are provided: (i) bounding boxes enclosing the crops of interest or their stems, weeds being left apart, and (ii) crop structures in the form of star graphs whose vertices are the plant organs (stems and leaves) and whose edges represent the connections between them. The images have been captured in various production and experimentation plots in France using an acquisition module which controls light conditions. They present a wide variety of soil conditions, weed infestation and growth stages. This dataset can benefit precision hoeing and in-field crop monitoring applications that are based on proximal imagery.Bloc-outil et Imagerie de Précision pour le Binage Intra-rang Précoc

Seismic Fault Preserving Diffusion

This paper focuses on the denoising and enhancing of 3-D reflection seismic data. We propose a pre-processing step based on a non linear diffusion filtering leading to a better detection of seismic faults. The non linear diffusion approaches are based on the definition of a partial differential equation that allows us to simplify the images without blurring relevant details or discontinuities. Computing the structure tensor which provides information on the local orientation of the geological layers, we propose to drive the diffusion along these layers using a new approach called SFPD (Seismic Fault Preserving Diffusion). In SFPD, the eigenvalues of the tensor are fixed according to a confidence measure that takes into account the regularity of the local seismic structure. Results on both synthesized and real 3-D blocks show the efficiency of the proposed approach.Comment: 10 page

Axis detection method for cylindrical objects

International audienceThis paper introduces an algorithm dedicated to the detection of the axes of cylindrical objects in a 3-D block. The proposed algorithm performs the 3-D axis detection without prior segmentation of the block. This approach is specifically appropriate when the grey levels of the cylindrical object are not homogeneous and thus difficult to distinguish from the background. The method relies on gradient and curvature estimation and operates in two main steps. The first one selects candidate voxels for the axis and the second one refines the determination of the axis of each cylindrical object. Applied to fiber reinforced composite materials, this algorithm allows detecting the axes of fibers in order to obtain the geometrical characteristics of the reinforcement. Knowing the reinforcement characteristics is an important issue in the quality control of the material but also in the prediction of the thermal and mechanical behavior. In this paper, the various steps of the algorithm are detailed. Then, results obtained with synthetic blocks and with blocks acquired by synchrotron X-ray microtomography on actual carbon-fiber reinforced carbon (C/C) composites are presented

Axis detection of cylindrical objects in 3-D images

This paper introduces an algorithm dedicated to the detection of the axes of cylindrical objects in a 3-D block. The proposed algorithm performs the 3-D axis detection without prior segmentation of the block. This approach is specifically appropriate when the grey levels of the cylindrical objects are not homogeneous and thus difficult to distinguish from the background. The method relies on gradient and curvature estimation and operates in two main steps. The first one selects candidate voxels for the axes and the second one refines the determination of the axis of each cylindrical object. Applied to fiber reinforced composite materials, this algorithm allows detecting the axes of fibers in order to obtain the geometrical characteristics of the reinforcement. Knowing the reinforcement characteristics is an important issue in the quality control of the material but also in the prediction of the thermal and mechanical performance. In this paper, the various steps of the algorithm are detailed. Then, some results are presented, obtained with both synthetic blocks and real data acquired by synchrotron X-ray micro tomography on carbon-fiber reinforced carbon composites. 2 hal-00326703, version 1- 5 Oct 2008 1

2D Fourier Transform Based Analysis Comparing the DFA with the DMA

International audienc

2D Fourier Transform Based Analysis Comparing the DFA with the DMA

International audienc

Robust and adaptive approaches for Relative Geologic Time Estimation

For a geoscientist, the Relative Geologic Time (RGT) is an important tool to perform chronostratigraphic analysis. However, automatically estimate an RGT image from a seismic image can be a challenging task where we have to respect seismic features, the deposit orders and to deal efficiently with unconformities such as erosions, progradating systems, etc. To this end, approaches have been proposed formulating the estimation problem in a regularized convex optimization problem. However none of these fully address efficiently all issues. In this paper, we propose a new regularization term based on an asymmetric and adaptive weight function. The asymmetric behavior focuses on the ill-posed problem while the adaptive process is used to deal with unconformities by modulating the strength of the regularization if necessary. Moreover, to increase the robustness of the approach, we propose variants of the method in terms of l(1)-norm instead of l(2)-norm that corresponds to potentially too smooth solutions. For evaluating the relevance of our proposals, experimentations have been conducted on both synthetic and real seismic images. (C) 2018 Elsevier B.V. All rights reserved