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Proceedings Paper

Ultrasonic imaging for non-destructive evaluation of standing trees: effect of anisotropy on image reconstruction
Author(s): Luis Espinosa; Flavio Prieto; Loïc Brancheriau
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Paper Abstract

Trees play a major ecological and sanitary role in modern cities. Nondestructive imaging methods allow to analyze the inner structures of trees, without altering their condition. In this study, we are interested on evaluating the influence of anisotropy condition in wood on the tomography image reconstruction using ultrasonic waves, by time-of-flight (TOF) estimation using the raytracing approach, a technique used particularly in the field of exploration seismography to simulate wave fronts in elastic media. Mechanical parameters from six wood species and one isotropic material were defined and their wave fronts and corresponding TOF values were obtained, using the proposed raytracing method. If the material presented anisotropy, the ray paths between the emitter and the receivers were not straight; therefore, curved rays were obtained for wood and the TOF measurements were affected. To obtain the tomographic image from the TOF measurements, the filtered back-projection algorithm was applied, a widely used technique in applications of straight ray tomography, but also commonly used in wood acoustic tomography. First, discs without inner defects for isotropic and wood materials (Spruce sample) were tested. Isotropic material resulted in a flat color image; for wood material, a gradient of velocities was obtained. After, centric and eccentric defects were tested, both for isotropic and orthotropic cases. From the results obtained for wood, when using a reconstruction algorithm intended for straight ray tomography, the images presented velocity variations from the border to the center that made difficult the discrimination of possible defects inside the samples, especially for eccentric cases.

Paper Details

Date Published: 14 May 2017
PDF: 8 pages
Proc. SPIE 10338, Thirteenth International Conference on Quality Control by Artificial Vision 2017, 1033808 (14 May 2017); doi: 10.1117/12.2266757
Show Author Affiliations
Luis Espinosa, Univ. Nacional de Colombia (Colombia)
CIRAD (France)
Flavio Prieto, Univ. Nacional de Colombia (Colombia)
Loïc Brancheriau, CIRAD (France)

Published in SPIE Proceedings Vol. 10338:
Thirteenth International Conference on Quality Control by Artificial Vision 2017
Hajime Nagahara; Kazunori Umeda; Atsushi Yamashita, Editor(s)

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