Autocalibration method for scanning electron microscope using affine camera model

Andrey Kudryavtsev (1) , Valerian Guelpa (1) , Patrick Rougeot (1) , Olivier Lehmann (1) , Sounkalo Dembele (1) , Peter Sturm (2) , Nadine Piat (1)

1 FEMTO-ST - Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174)
2 STEEP - Sustainability transition, environment, economy and local policy

This paper deals with the task of autocalibration of scanning electron microscope (SEM), which is a technique allowing to compute camera motion and intrinsic parameters. In contrast to classical calibration, which implies the use of a calibration object and is known to be a tedious and rigid operation, auto- or selfcalibration is performed directly on the images acquired for the visual task. As autocalibration represents an optimization problem, all the steps contributing to the success of the algorithm are presented: formulation of the cost function incorporating metric constraints, definition of bounds, regularization, and optimization algorithm. The presented method allows full estimation of camera matrices for all views in the sequence. It was validated on virtual images as well as on real SEM images (pollen grains, cutting tools, etc.). The results show a good convergence range and low execution time, notably compared to classical methods, and even more in the context of the calibration of SEM.

Domaines: Automatique / Robotique; Algorithme et structure de données [cs.DS]

Andrey Kudryavtsev, Valerian Guelpa, Patrick Rougeot, Olivier Lehmann, Sounkalo Dembele, et al.. Autocalibration method for scanning electron microscope using affine camera model. Machine Vision and Applications, 2020, 31 (7), pp.1 -15. ⟨10.1007/s00138-020-01109-x⟩. ⟨hal-02993826⟩