1. Autocalibration method for scanning electron microscope using affine camera model
- Author
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Nadine Le Fort-Piat, Peter Sturm, Valerian Guelpa, Olivier Lehmann, Sounkalo Dembélé, Andrey V. Kudryavtsev, Patrick Rougeot, Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST), Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS), Sustainability transition, environment, economy and local policy (STEEP), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), and ANR-17-EURE-0002,EIPHI,Ingénierie et Innovation par les sciences physiques, les savoir-faire technologiques et l'interdisciplinarité(2017)
- Subjects
Optimization problem ,Computer science ,[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS] ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Context (language use) ,02 engineering and technology ,Regularization (mathematics) ,[SPI.AUTO]Engineering Sciences [physics]/Automatic ,03 medical and health sciences ,Convergence (routing) ,0202 electrical engineering, electronic engineering, information engineering ,Calibration ,Computer vision ,030304 developmental biology ,0303 health sciences ,business.industry ,Computer Science Applications ,Hardware and Architecture ,Virtual image ,Metric (mathematics) ,020201 artificial intelligence & image processing ,Computer Vision and Pattern Recognition ,Affine transformation ,Artificial intelligence ,business ,Software - Abstract
International audience; 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.
- Published
- 2020
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