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DESIGNING A SEMI-AUTOMATED AND REMOTE SYSTEM TO RETRIEVE VARVED IMAGES FROM THIN-SECTIONS AT THE SCANNING ELECTRON MICROSCOPE.

FRANCUS, PIERRE  INRS-Centre Eau, Terre et Environnement.

Paleoenvironmental reconstructions from long (>500 years) varved sequences using image analysis techniques have a strong potential to increase our knowledge of climate variability (Francus et al., 2002). In Arctic lakes that contain little biogenic remains, textural analysis at the varve scale is often the only way to obtain reliable information about past environments. However, the acquisition and the processing of a large number of images is quite a tedious task even if the existing algorithms are efficient.

In this poster, we present the design of a system that will allow the semi-automated acquisition and processing of images of individual varve from thin-section. The system will be designed around a Scanning Electron Microscope (SEM) using its backscattered electron detector.

First, the user needs to cut a thin-section from sediment, including some positioning jigs. Then, the user will mark manually the Region of Interest (ROI) on a flat bed scanner image of the thin-sections or a photo mosaic taken at the SEM at low magnification. The system will drive a motorized stage in order to take a high quality image of the ROI. The automated acquisition system should be able to correct for the drift of the SEM. For calibration and laboratory intercomparison purposes, some reference materials that have a wide range of backscattered coefficients will be embedded in the sample holder itself. The system should acquire an image of reference material every 10-20 images for calibration purpose (Soreghan and Francus, in press). Then the ROI will be processed using image analysis routines (Francus, 1998). All images, data and metadata will be stored in a customized database in order to allow the user to easily compile a long paleoenvironmental sequence. By using the same database for holding sample information, defining processing requirements and for holding results, it will be possible to examine and verify the entire processing chain that was used to calculate any and all results (audit trail).

In order to allow for collaborative work, the system will be accessible through a web interface: users should be able to design and run an experiment remotely. They will just have to send their set of thin-sections to our facility and an operator will place them in the SEM chamber. However, it will be the user's responsibility to assess the annual character of the laminations.

Finally, since the system is still in development, I do welcome any suggestions from potential users to increase the usefulness of the system.

REFERENCES
Francus, P., Bradley, S., Abbott, M., Patridge, W., & Keimig F., 2002. Paleoclimate studies of minerogenic sediments using annually resolved textural parameters: Geophysical Research Letters, v. 29, 20, 1998.

Francus, P., 1998. An image analysis technique to measure grain-size variation in thin sections of soft clastic sediments: Sedimentary Geology, v. 121, p. 289-298.

Soreghan, M., & Francus, P., BSE thin-sections studies: In: Francus, P., (Editor), Image Analysis, Sediments and Paleoenvironments, Kluwer Academic Publishers, Dordrecht, The Netherlands, in press.


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