Computer vision methods for optical microscopes

Boissenin, M.; Wedekind, Jan; Selvan, Arul; Amavasai, B.P.; Caparrelli, Fabio; Travis, J.R.

doi:10.1016/j.imavis.2006.03.009

Cited by 32 publications

(16 citation statements)

References 7 publications

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“…The spatial position of the AFM-tip is determined from the position of the micromanipulator on the assumption that the x−y−z piezoelectric positioning stage is very precise (closedloop control) with a nanometer positioning accuracy. In order to recover the position of the AFM-tip with high accuracy, we choose the image normalized correlation technique [20] which is fast, invariant to linear radiometric changes and can be implemented in a context of Kalman filtering (Gaussian noise assumptions) [23] or particle filtering (nonGaussian noise assumptions) [24]. Methods such as wavelet decomposition may be used to improve the tracking precision with a multi-resolution and auto-focusing approach [25].…”

Section: B High-accuracy Target Constructionmentioning

confidence: 99%

Automatic Camera-Based Microscope Calibration for a Telemicromanipulation System Using a Virtual Pattern

2009

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Abstract-In the context of virtualized-reality-based telemicromanipulation, this paper presents a visual calibration technique for an optical microscope coupled to a CCD camera. The accuracy and flexibility of the proposed automatic virtual calibration method, based on Parallel Single-Plane properties, are outlined. In contrast to standard approaches, a 3D virtual calibration pattern is constructed using the micromanipulator tip with subpixel-order localization in the image frame. The proposed procedure leads to a linear system whose solution provides directly both the intrinsic and extrinsic parameters of the geometrical model. Computer simulations and real data have been used to test the proposed technique, and promising results have been obtained. Based on the proposed calibration techniques, a 3D virtual microenvironment of the workspace is reconstructed through the real-time imaging of two perpendicular optical microscopes. Our method provides a flexible, easy-touse technical alternative to the classical techniques used in micromanipulation systems.

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Section: B High-accuracy Target Constructionmentioning

confidence: 99%

Automatic Camera-Based Microscope Calibration for a Telemicromanipulation System Using a Virtual Pattern

2009

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“…The technique of SFF is primarily useful in places where there are space constraints and installing more than one camera is not feasible. The technique has been successfully used in the area of microrobotics [13], medical diagnostics, and petrological and mineralogical research [14] [15]. Sahay et al [16] [17] recently extended the SFF framework for super resolving the depth profile and focused image.…”

Section: Introductionmentioning

confidence: 99%

Underwater Microscopic Shape from Focus

Karthik

Rajagopalan

2014

2014 22nd International Conference on Pattern Recognition

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In this paper, we extend traditional Shape from focus (SFF) to the underwater scenario. Specifically, we show how 3D shape of objects immersed in water can be extracted from images captured under an optical microscope. Traditional SFF employs telecentric optics to achieve geometric registration among the frames. We extend conventional SFF to underwater objects under the assumption of negligible scattering. We establish that the property of telecentricity holds for objects immersed in water provided the numerical aperture is small. By modeling geometrical distortions due to refraction effects on the water surface, we prove that the depth map obtained in the presence of water is a scaled version of the original depth map. We also reveal that this scale factor is directly related to the refractive index of water. We validate performance with real experiments.

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“…The SFF technique has been successfully utilized in many industrial applications, i.e. microelectronics [29], industrial inspection [33], medical diagnostics [5], 3D cameras [23], TFT-LCD color filter manufacturing [2], and comparison of polymers [26].…”

Section: Introductionmentioning

confidence: 99%