Personne :
Fleuret, Julien

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Adresse électronique
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Université Laval. Département de génie électrique et de génie informatique
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Voici les éléments 1 - 6 sur 6
  • Publication
    Accès libre
    Non-destructive investigation of paintings on canvas by continuous wave terahertz imaging and flash thermography
    (Springer, 2017-04-05) Avdelidis, Nicolas P.; Fleuret, Julien; Saluja, Karan; Zhang, Hai; Peeters, Jeroen; Maldague, X.; Ibarra Castanedo, Clemente; Duan, Yuxia; Sfarra, Stefano; Fernandes, Henrique
    Terahertz (THz) imaging is increasingly used in the cultural heritage field. In particular, continuous wave (CW) and low frequency THz is attracting more attention. The first application of the THz technique inherent to the cultural heritage field dates back 10 years ago. Since 2006, tangible improvements have been conducted in the refinement of the technique, with the aim to produce clear maps useful for any art restorer. In this paper, a CW THz (0.1 THz) imaging system was used to inspect paintings on canvas both in reflection and in transmission modes. In particular, two paintings were analyzed: in the first one, similar materials and painting execution of the original artwork were used, while in the second one, the canvas layer is slightly different. Flash thermography was used herein together with the THz method in order to observe the differences in results for the textile support materials. A possible application of this method for the detection of artwork forgery requires some parameterization and analysis of various materials or thickness influence which will be addressed in a future study. In this work, advanced image processing techniques including principal component thermography (PCT) and partial least squares thermography (PLST) were used to process the infrared data. Finally, a comparison of CW THz and thermographic results was conducted.
  • Publication
    On the use of pulsed thermography signal reconstruction based on linear support vector regression for carbon fiber reinforced polymer inspection
    (Lavoisier, 2022-02-07) Fleuret, Julien; Ebrahimi, Samira; Maldague, X.; Ibarra Castanedo, Clemente
    This study introduces and evaluates a new approach to reconstruct image sequences acquired during non-destructive testing by pulsed thermography. The proposed method consists of applying two linear support vector regressions to model the evolution of the data from both a spatial and temporal point of view. Each regression vectors will map the data with the number of pixels and the number of frames using convex optimisation. Then the regression vectors are used to predict a more robust representation of the data, thus reconstructing the sequence. The proposed method has been applied to data related to a reference sample of carbon reinforced fibre with known defects. This approach was evaluated on a sequence with severe non-uniform heating and was compared with state-of-the-art methods. Despite being sensitive to nonuniform heating, the proposed method provided a higher CNR score on smaller defects, compared with state-of-the-art methods. For the shallowest defects it shows better performance in term of contrast reconstruction compared to partial least-squares thermography (PLST). It also outperforms principal component thermography (PCT), and thermographic signal reconstruction-PCT (TSR-PCT) for defects located at a depth of 0.6 mm and 0.8 mm below the surface.
  • Publication
    Accès libre
    Pulsed micro-laser line thermography on submillimeter porosity in carbon fiber reinforced polymer composites : experimental and numerical analyses for the capability of detection
    (Optical Society of America, 2016-08-08) Fleuret, Julien; Zhang, Hai; Maldague, X.; Hassler, Ulf; Ibarra Castanedo, Clemente; Robitaille, François; Djupkep Dizeu, Frank Billy; Genest, Marc; Fernandes, Henrique; Joncas, Simon
    In this article, pulsed micro-laser line thermography (pulsed micro-LLT) was used to detect the submillimeter porosities in a 3D preformed carbon fiber reinforced polymer composite specimen. X-ray microcomputed tomography was used to verify the thermographic results. Then, finite element analysis was performed on the corresponding models on the basis of the experimental results. The same infrared image processing techniques were used for the experimental and simulation results for comparative purposes. Finally, a comparison of experimental and simulation postprocessing results was conducted. In addition, an analysis of probability of detection was performed to evaluate the detection capability of pulsed micro-LLT on submillimeter porosity.
  • Publication
    Accès libre
    Automated assessment and tracking of human body thermal variations using unsupervised clustering
    (The Optical Society of America, 2016-11-17) Fleuret, Julien; Zhang, Hai; Maldague, X.; Yousefi, Bardia; Watt, Raymond; Klein, Matthieu
    The presented approach addresses a review of the overheating that occurs during radiological examinations, such as magnetic resonance imaging, and a series of thermal experiments to determine a thermally suitable fabric material that should be used for radiological gowns. Moreover, an automatic system for detecting and tracking of the thermal fluctuation is presented. It applies hue-saturated-value-based kernelled k-means clustering, which initializes and controls the points that lie on the region-of-interest (ROI) boundary. Afterward, a particle filter tracks the targeted ROI during the video sequence independently of previous locations of overheating spots. The proposed approach was tested during experiments and under conditions very similar to those used during real radiology exams. Six subjects have voluntarily participated in these experiments. To simulate the hot spots occurring during radiology, a controllable heat source was utilized near the subject’s body. The results indicate promising accuracy for the proposed approach to track hot spots. Some approximations were used regarding the transmittance of the atmosphere, and emissivity of the fabric could be neglected because of the independence of the proposed approach for these parameters. The approach can track the heating spots continuously and correctly, even for moving subjects, and provides considerable robustness against motion artifact, which occurs during most medical radiology procedures.
  • Publication
    Accès libre
    Unsupervised automatic tracking of thermal changes in human body
    (Optical Society of America, 2015-09-30) Jo, Marcelo Sung Ma; Labrie-Larrivée, Félix; Fleuret, Julien; Maldague, X.; Fréchet, Simon; Ghaffari, Seyed Alireza; Yousefi, Bardia; Watt, Raymond
    An automated system for detecting and tracking of the thermal fluctuation in human body is addressed. It applies HSV based k-means clustering which initialized and controlled the points which lie on the ROI boundary. Afterward a particle filter tracked the targeted ROI in the thermal video stream. There were six subjects have voluntarily participated on these experiments. For simulating the hot spots occur during the some medical tests a controllable heater utilized close to the subjects body. The results indicated promising accuracy of the proposed approach for tracking the hot spots. However, there were some approximations (e.g. the transmittance of the atmosphere and emissivity of the fabric) which can be neglected because of independency of the proposed approach for these parameters. The approach can track the heating spots efficiently considering the movement in the subjects which provided a confidence of considerable robustness against motion-artifact usually occurs in the medical tests.
  • Publication
    Accès libre
    Artificial vision by thermography : calving prediction and defect detection in carbon fiber reinforced polymer
    (2021) Fleuret, Julien; Maldague, X.
    La vision par ordinateur est un domaine qui consiste à extraire ou identifier une ou plusieurs informations à partir d'une ou plusieurs images dans le but soit d'automatiser une tache, soit de fournir une aide à la décision. Avec l'augmentation de la capacité de calcul des ordinateurs, la vulgarisation et la diversification des moyens d'imagerie tant dans la vie quotidienne, que dans le milieu industriel, ce domaine a subi une évolution rapide lors de dernières décennies. Parmi les différentes modalités d'imagerie pour lesquels il est possible d'utiliser la vision artificielle cette thèse se concentre sur l'imagerie infrarouge. Plus particulièrement sur l'imagerie infrarouge pour les longueurs d'ondes comprises dans les bandes moyennes et longues. Cette thèse se porte sur deux applications industrielles radicalement différentes. Dans la première partie de cette thèse, nous présentons une application de la vision artificielle pour la détection du moment de vêlage en milieux industriel pour des vaches Holstein. Plus précisément l'objectif de cette recherche est de déterminer le moment de vêlage en n'utilisant que des données comportementales de l'animal. À cette fin, nous avons acquis des données en continu sur différents animaux pendant plusieurs mois. Parmi les nombreux défis présentés par cette application l'un d'entre eux concerne l'acquisition des données. En effet, les caméras que nous avons utilisées sont basées sur des capteurs bolométriques, lesquels sont sensibles à un grand nombre de variables. Ces variables peuvent être classées en quatre catégories : intrinsèque, environnemental, radiométrique et géométrique. Un autre défit important de cette recherche concerne le traitement des données. Outre le fait que les données acquises utilisent une dynamique plus élevée que les images naturelles ce qui complique le traitement des données ; l'identification de schéma récurrent dans les images et la reconnaissance automatique de ces derniers grâce à l'apprentissage automatique représente aussi un défi majeur. Nous avons proposé une solution à ce problème. Dans le reste de cette thèse nous nous sommes penchés sur la problématique de la détection de défaut dans les matériaux, en utilisant la technique de la thermographie pulsée. La thermographie pulsée est une méthode très populaire grâce à sa simplicité, la possibilité d'être utilisée avec un grand nombre de matériaux, ainsi que son faible coût. Néanmoins, cette méthode est connue pour produire des données bruitées. La cause principale de cette réputation vient des diverses sources de distorsion auquel les cameras thermiques sont sensibles. Dans cette thèse, nous avons choisi d'explorer deux axes. Le premier concerne l'amélioration des méthodes de traitement de données existantes. Dans le second axe, nous proposons plusieurs méthodes pour améliorer la détection de défauts. Chaque méthode est comparée à plusieurs méthodes constituant l'état de l'art du domaine.