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Three-dimensional reconstruction of highly complex microscopic samples using scanning electron microscopy and optical flow estimation

View Article: PubMed Central - PubMed

ABSTRACT

Scanning Electron Microscope (SEM) as one of the major research and industrial equipment for imaging of micro-scale samples and surfaces has gained extensive attention from its emerge. However, the acquired micrographs still remain two-dimensional (2D). In the current work a novel and highly accurate approach is proposed to recover the hidden third-dimension by use of multi-view image acquisition of the microscopic samples combined with pre/post-processing steps including sparse feature-based stereo rectification, nonlocal-based optical flow estimation for dense matching and finally depth estimation. Employing the proposed approach, three-dimensional (3D) reconstructions of highly complex microscopic samples were achieved to facilitate the interpretation of topology and geometry of surface/shape attributes of the samples. As a byproduct of the proposed approach, high-definition 3D printed models of the samples can be generated as a tangible means of physical understanding. Extensive comparisons with the state-of-the-art reveal the strength and superiority of the proposed method in uncovering the details of the highly complex microscopic samples.

No MeSH data available.


Relationship between the estimated height (h) and the computed horizontal disparity (d) using the pixel size in sample units (p) and the total tilt angle (θ).
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pone.0175078.g003: Relationship between the estimated height (h) and the computed horizontal disparity (d) using the pixel size in sample units (p) and the total tilt angle (θ).

Mentions: The horizontal disparity computed from the previous step, can be utilized for estimating the depth of the individual pixels contained in the images. This requires several parameters to be known: tilt angle, magnification factor and size of each pixel in sample units. Fig 3 shows the relationship between the computed horizontal disparity and the height for a few sample points. This can be represented using a simple trigonometric equation [61–63]:h=d.p2sin(θ2)(16)which uses the computed horizontal disparity d, pixel size in sample units (p) and the total tilt angle (θ) to estimate the height (h).


Three-dimensional reconstruction of highly complex microscopic samples using scanning electron microscopy and optical flow estimation
Relationship between the estimated height (h) and the computed horizontal disparity (d) using the pixel size in sample units (p) and the total tilt angle (θ).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5383242&req=5

pone.0175078.g003: Relationship between the estimated height (h) and the computed horizontal disparity (d) using the pixel size in sample units (p) and the total tilt angle (θ).
Mentions: The horizontal disparity computed from the previous step, can be utilized for estimating the depth of the individual pixels contained in the images. This requires several parameters to be known: tilt angle, magnification factor and size of each pixel in sample units. Fig 3 shows the relationship between the computed horizontal disparity and the height for a few sample points. This can be represented using a simple trigonometric equation [61–63]:h=d.p2sin(θ2)(16)which uses the computed horizontal disparity d, pixel size in sample units (p) and the total tilt angle (θ) to estimate the height (h).

View Article: PubMed Central - PubMed

ABSTRACT

Scanning Electron Microscope (SEM) as one of the major research and industrial equipment for imaging of micro-scale samples and surfaces has gained extensive attention from its emerge. However, the acquired micrographs still remain two-dimensional (2D). In the current work a novel and highly accurate approach is proposed to recover the hidden third-dimension by use of multi-view image acquisition of the microscopic samples combined with pre/post-processing steps including sparse feature-based stereo rectification, nonlocal-based optical flow estimation for dense matching and finally depth estimation. Employing the proposed approach, three-dimensional (3D) reconstructions of highly complex microscopic samples were achieved to facilitate the interpretation of topology and geometry of surface/shape attributes of the samples. As a byproduct of the proposed approach, high-definition 3D printed models of the samples can be generated as a tangible means of physical understanding. Extensive comparisons with the state-of-the-art reveal the strength and superiority of the proposed method in uncovering the details of the highly complex microscopic samples.

No MeSH data available.