Abstract-Shape-from-focus for real-time terahertz 3D imaging

J.-B. Perraud, J. P. Guillet, O. Redon, M. Hamdi, F. Simoens, and P. Mounaix

https://www.osapublishing.org/ol/abstract.cfm?uri=ol-44-3-483

Thanks to significant advances in real-time terahertz imaging in terms of resolution and image quality, adapting and extending optical methods for 3D imaging at the millimeter scale is now promising. The shape-from-focus algorithm is a post-processing tool used in optical microscopy to reconstruct the external shape surface of a convex surface object. Images acquired at different distances from the object-side focal plane are implemented in this algorithm. We localize the best focus position in the stack of images for each pixel and then reconstruct the object in 3D due to the short depth of field. In this Letter, we propose an application of this algorithm in active and real-time terahertz imaging. We achieve the experimental reconstruction in 3D with a terahertz waves imaging system composed of a powerful source and a real-time terahertz camera.

Abstract-Shape-from-focus for real-time terahertz 3D imaging

J.-B. Perraud, J.-P. Guillet, O. Redon, M. Hamdi, F. Simoens, P. Mounaix,

https://www.osapublishing.org/ol/abstract.cfm?uri=ol-44-3-483

Thanks to significant advances in real-time terahertz imaging in terms of resolution and image quality, adapting and extending optical methods for 3D imaging at the millimeter scale is now promising. The shape-from-focus algorithm is a post-processing tool used in optical microscopy to reconstruct the external shape surface of a convex surface object. Images acquired at different distances from the object-side focal plane are implemented in this algorithm. We localize the best focus position in the stack of images for each pixel and then reconstruct the object in 3D due to the short depth of field. In this Letter, we propose an application of this algorithm in active and real-time terahertz imaging. We achieve the experimental reconstruction in 3D with a terahertz waves imaging system composed of a powerful source and a real-time terahertz camera.

Abstract-2D and 3D Terahertz Imaging and X-Rays CT for Sigillography Study

• M. Fabre, 
• R. Durand, 
• L. Bassel, 
• B. Recur, 
• H. Balacey, 
• J. Bou Sleiman, 
• J.-B. Perraud, 
• P. Mounaix, 

http://link.springer.com/article/10.1007%2Fs10762-017-0356-3

Seals are part of our cultural heritage but the study of these objects is limited because of their fragility. Terahertz and X-Ray imaging are used to analyze a collection of wax seals from the fourteenth to eighteenth centuries. In this work, both techniques are compared in order to discuss their advantages and limits and their complementarity for conservation state study of the samples. Thanks to 3D analysis and reconstructions, defects and fractures are detected with an estimation of their depth position. The path from the parchment tongue inside the seals is also detected.

Abstract-Discrimination and identification of RDX/PETN explosives by chemometrics applied to terahertz time-domain spectral imaging

J. Bou-Sleiman, J.-B. Perraud, J.-P. Guillet, P. Mounaix

IMS, CNRS, Bordeaux Univ. (France)

B. Bousquet

CELIA, CNRS, Bordeaux Univ. (France)

N. Palka

Military Univ. of Technology (Poland)

Proc. SPIE 9651, Millimetre Wave and Terahertz Sensors and Technology VIII, 965109 (October 21, 2015); doi:10.1117/12.2197442

http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=2466618

Detection of explosives has always been a priority for homeland security. Jointly, terahertz spectroscopy and imaging are emerging and promising candidates as contactless and safe systems. In this work, we treated data resulting from hyperspectral imaging obtained by THz-time domain spectroscopy, with chemometric tools. We found efficient identification and sorting of targeted explosives in the case of pure and mixture samples. In this aim, we applied to images Principal Component Analysis (PCA) to discriminate between RDX, PETN and mixtures of the two materials, using the absorbance as the key-parameter. Then we applied Partial Least Squares-Discriminant Analysis (PLS-DA) to each pixel of the hyperspectral images to sort the explosives into different classes. The results clearly show successful identification and categorization of the explosives under study.
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