Robust surface reconstruction in SEM with Two BSE detectors

Chen, Deshan; Miyamoto, Atsushi; Kaneko, Shun’ichi

doi:10.1109/mecatronics.2012.6450989

Cited by 5 publications

(2 citation statements)

References 12 publications

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“…Over the past few years there has been an expansion in the designing of 3D surface reconstruction algorithms for SEM images. All these algorithms are classified into two categories: single-view and multi-view [7], [15], [22], [23], [26]. In 2007 Samak et al [23] used a multiple view geometry algorithm to reconstruct 3D micro structure surfaces from SEM images.…”

Section: Introductionmentioning

confidence: 99%

3D Microscopy Vision Using Multiple View Geometry and Differential Evolutionary Approaches

Tafti

Kirkpatrick

Owen

et al. 2014

Advances in Visual Computing

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Abstract. The Scanning Electron Microscope (SEM) as 2D imaging equipment has been widely used in biology and material sciences to determine the surface attributes of a microscopic object. Having 3D surfaces from SEM images would provide true anatomic shapes of micro samples which allow for quantitative measurements and informative visualization of the systems being investigated. In this contribution, we present a Differential Evolutionary (DE) approach for both SEM extrinsic calibration and 3D surface reconstruction. We show that the SEM extrinsic calibration and its 3D shape model can be accurately estimated in a global optimization platform. Several experiments from various perspectives are performed on real and synthetic data to validate the speed, reliability and accuracy of the proposed system. The present work is expected to stimulate more interest and draw attentions from the computer vision community to the fast-growing SEM application area.

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Section: Introductionmentioning

confidence: 99%

3D Microscopy Vision Using Multiple View Geometry and Differential Evolutionary Approaches

Tafti

Kirkpatrick

Owen

et al. 2014

Advances in Visual Computing

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“…In [8], a laser triangulation method has been used for depth detection utilizing an additional optical microscope. A photometric stereo-based approach using multiple back scattered electron detectors has been used in [9].…”

Section: Introductionmentioning

confidence: 99%

Depth and Shape estimation from focus in scanning electron microscope for micromanipulation

Marturi

Dembélé

Piat

2013

2013 International Conference on Control, Automation, Robotics and Embedded Systems (CARE)

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Abstract-Inter-object depth estimation is always a major concern for micromanipulation using scanning electron microscope (SEM). So far, various methods have been proposed for estimating this depth based on stereoscopic imaging. Most of them require external hardware unit or manual interaction during the process. In this paper, using the image focus information, different methods are presented for estimating the inter-object depth for micromanipulation and the local pixel point depth for 3D shape reconstruction. In both cases, the normalized variance has been used as the sharpness criteria. For interobject depth estimation, a visual servoing-based autofocusing method has been used to maximize the sharpness in object region windows. For Shape reconstruction, a stack of images are acquired by varying the working distance. These images are processed to find the maximum sharpness of each pixel and consequently reconstructing the surface. Developments are validated in a robotic handling scenario where the scene contains a microgripper and silicon microstructures.

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Reconstruction algorithm of 3D surface in scanning electron microscopy with backscattered electron detector

Borzunov

Lukyanenko

Рау

et al. 2021

Journal of Inverse and Ill-Posed Problems

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Robust surface reconstruction in SEM with Two BSE detectors

Cited by 5 publications

References 12 publications

3D Microscopy Vision Using Multiple View Geometry and Differential Evolutionary Approaches

3D Microscopy Vision Using Multiple View Geometry and Differential Evolutionary Approaches

Depth and Shape estimation from focus in scanning electron microscope for micromanipulation

Reconstruction algorithm of 3D surface in scanning electron microscopy with backscattered electron detector

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