is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. Abstract:In this paper, a new approach to computing the deviation of wood grain is proposed. To do this, the thermal conduction properties of timber are used (higher conduction in the fiber direction). Exciting the surface of the wood with a laser and capturing the thermal conduction using a thermal camera, an ellipse can be observed. Using a method similar to the tracheid effect, it is possible to extract information from this ellipse, such as the slope of grain and the presence of knots. With this method it is therefore possible to extend the mechanical model (assessing the mechanical properties of timber) to take certain singularities into account. Using this approach, the slope of grain can be estimated for any wood species, either hardwood or softwood, which was not possible with the existing tracheid effect. References and links
The EU imposes standards for the use of wood in structural applications. Local singularities such as knots affect the wood mechanical properties. They can be revealed by looking at the wood fiber orientation. For this reason, many methods were proposed to estimate the orientation of wood fiber using optical means, X-rays, or scattering measurement techniques. In this paper, an approach to assess the wood fiber orientation based on thermal ellipsometry is developed. The wood part is punctually heated with a Nd-YAG Laser and the thermal response is acquired by an infrared camera. The thermal response is elliptical due to the propagation of the heat through and along the wood fibers. An experiment is presented to show the capacity of such techniques to assess fiber orientation on wood specimen. In addition, an appropriate algorithm is given to extract the orientation of the ellipse.
To cite this version:V Daval, Olivier Aubreton, Frédéric Truchetet. Coarse to fine : toward an intelligent 3D acquisition system. Three-Dimensional Image Processing, Measurement (3DIPM), and Applications 2015, SPIE, Feb 2015 Coarse to fine: toward an intelligent 3D acquisition system V. Daval, O. Aubreton, F. Truchetet Le2i,UMR 6306 CNRS-Université de Bourgogne, France ABSTRACTThe 3D acquisition-compression-processing chain is, most of the time, sequenced into independent stages. As resulting, a large amount of 3D points are acquired whatever the geometry of the object and the processing to be done in further steps. It appears, particularly in mechanical part 3D modeling and in CAD, that the acquisition of such an amount of data is not always mandatory. We propose a method aiming at minimizing the number of 3D points to be acquired with respect to the local geometry of the part and therefore to compress the cloud of points during the acquisition stage. The method we propose is based on a new coarse to fine approach in which from a coarse set of 2D points associated to the local normals the 3D object model is segmented into a combination of primitives. The obtained model is enriched where it is needed with new points and a new primitive extraction stage is performed in the refined regions. This is done until a given precision of the reconstructed object is attained. It is noticeable that contrary to other studies we do not work on a meshed model but directly on the data provided by the scanning device.
The 3D chain (acquisition-processing-compression) is, most of the time, sequenced into several steps. Such approaches result into an one-dense acquisition of 3D points. In large scope of applications, the first processing step consists in simplifying the data. In this paper, we propose a coarse to fine acquisition system which permits to obtain simplified data directly from the acquisition. By calculating some complementary information from 2D images, such as 3D normals, multiple homogeneous regions will be segmented and affected to a given primitive class. Contrary to other studies, the whole process is not based on a mesh. The obtained model is simplified directly from the 2D data acquired by a 3D scanner.
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