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Research Papers

Algorithms for Extraction of Nanowire Lengths and Positions From Optical Section Microscopy Image Sequence

[+] Author and Article Information
Tao Peng

Department of Mechanical Engineering, University of Maryland, College Park, MD 20742taopeng75@gmail.com

Arvind Balijepalli

Manufacturing Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899; Department of Mechanical Engineering, University of Maryland, College Park, MD 20742arvind.balijepalli@nist.gov

Satyandra K. Gupta

Department of Mechanical Engineering, University of Maryland, College Park, MD 20742; Institute for Systems Research, University of Maryland, College Park, MD 20742skgupta@umd.edu

Thomas W. LeBrun

Manufacturing Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899thomas.lebrun@nist.gov

J. Comput. Inf. Sci. Eng 9(4), 041007 (Nov 24, 2009) (11 pages) doi:10.1115/1.3249573 History: Received June 20, 2008; Revised February 09, 2009; Published November 24, 2009; Online November 24, 2009

This paper presents algorithms for estimating length, location, and orientation of nanowires in a fluidic workspace using images obtained by optical section microscopy. Images containing multiple nanowires are first segmented to locate general areas of interest, which are then analyzed to determine discrete nanowire parameters. We use a set of image processing techniques to extract features of nanowire image patterns, e.g., boundary of nanowire, linear edges, and the intensity profile of nanowire’s diffraction fringes. The parameters of the features are then used to estimate length, 3D position, and 3D orientation of nanowires. A scene representing the workspace is reconstructed using the estimated attributes of nanowires, and it is constantly updated upon the capture of every image frame. We believe that the work described in this paper will be useful for assembly of nanowires using optical tweezers.

Copyright © 2009 by American Society of Mechanical Engineers
Topics: Algorithms , Nanowires
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References

Figures

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Figure 1

Images of nanowires with different tilt angles

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Figure 2

Flowchart of the processing cycle to reconstruct 3D scene of nanowires

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Figure 3

Extracting the linear edge features in wire image using Hough transform

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Figure 4

Hough transform result of different wire images

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Figure 5

Definition of metadata

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Figure 6

Locating the boundary of nanowire image

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Figure 7

Finding an oriented bounding box for nanowire image

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Figure 8

Located end positions of a stationary wire in a stack of images

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Figure 9

Locating the waist position of nanowire image

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Figure 10

Located waist positions of a stationary nanowire in a stack of images

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Figure 11

Extracted swing angles (θP) of a stationary nanowire in a stack of images (unit for ZRel is μm)

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Figure 12

Extracting signature curves of nanowire image

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Figure 13

Relationship between θ and θP obtained from images of nanowire 1

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Figure 14

Relationship between wS¯ and Δz for three different nanowires

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Figure 15

Relationship between SF2 and Δz for three different nanowires

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Figure 16

Estimation of the z-position of a nanowire

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Figure 17

Frames of an example of scene reconstruction

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