Detecting Subsurface Circular Objects from Low Contrast Noisy Images: Applications in Microscope Image Enhancement

Particle detection in very noisy and low contrast images is an active field of research in image processing. In this article, a method is proposed for the efficient detection and sizing of subsurface spherical particles, which is used for the processing of softly fused Au nanoparticles. Transmission Electron Microscopy is used for imaging the nanoparticles, and the proposed algorithm has been tested with the two-dimensional projected TEM images obtained. Results are compared with the data obtained by transmission optical spectroscopy, as well as with conventional circular object detection algorithms.

Authors:

• Soham De
• Nupur Biswas
• Abhijit Sanyal
• Pulak Ray
• Alokmay Datta

Keywords:

• Transmission Electron Microscopy
• Circular Hough Transform
• Au Nanoparticles
• Median Filter
• Laplacian Sharpening Filter
• Canny Edge Detection

References:

[1] William V Nicholson and Robert M Glaeser. Review: Automatic
particle detection in electron microscopy. Journal of Structural Biology,
133(2/3):90-101, 2001.
[2] Richard O Duda and Peter E Hart. Use of the Hough transformation
to detect lines and curves in pictures. Communications of the ACM,
15(1):11-15, 1972.
[3] Paul V C Hough. Method and means for recognizing complex patterns,
1962.
[4] G H Woehrle, J E Hutchison, S Ozkar, and R G Finke. Analysis of
nanoparticle Transmission Electron Microscopy data using a publicdomain
image-processing program, Image. Turkish Journal of Chemistry,
30(1):1-13, 2006.
[5] R Fisker, J M Carstensen, M F Hansen, F B├© dker, and S M├© rup.
Estimation of nanoparticle size distributions by image analysis. Journal
of Nanoparticle Research, 2(3):267-277, 2000.
[6] A. Saad, W. Chiu, and P. Thuman-Commike. Multiresolution approach
to automatic detection of spherical particles from electron cryomicroscopy
images. In ICIP 98. Proceedings. International Conference
on Image Processing, pages 846-850, 1998.
[7] Rafael C Gonzalez and Richard E Woods. Digital Image Processing,
volume 49 of Texts in Computer Science. Prentice Hall, 2008.
[8] K R Lata, P Penczek, and J Frank. Automatic particle picking from
electron micrographs. Ultramicroscopy, 58(3-4):381-391, 1995.
[9] G Harauz and A Fong-Lochovsky. Automatic selection of macromolecules
from electron micrographs by component labelling and symbolic
processing. Ultramicroscopy, 31(4):333-344, 1989.
[10] Dana H Ballard and Christopher M Brown. Computer Vision, volume
Computer S. Prentice Hall, 1982.
[11] J Canny. A Computational Approach to Edge Detection. IEEE
Transactions on Pattern Analysis and Machine Intelligence, 8(6):679-
698, 1986.
[12] Mathias Brust, Merryl Walker, Donald Bethell, David J Schiffrin, and
Robin Whyman. Synthesis of thiol-derivatised gold nanoparticles in
a two-phase Liquid-Liquid system. Journal of the Chemical Society
Chemical Communications, 1994(7):801, 1994.
[13] Mathias Brust, David J Schiffrin, Donald Bethell, and Christopher J
Kiely. Novel gold-dithiol nano-networks with non-metallic electronic
properties. Advanced Materials, 7(9):795-797, 1995.
[14] J Perenboom. Electronic properties of small metallic particles. Physics
Reports, 78(2):173-292, 1981.
[15] Lorenza Suber. Permanent Magnetism in Dithiol-Capped Silver
Nanoparticles. Chemistry of Materials, 19(6):1509-1517, 2007.
[16] Marcin Smereka and Ignacy Dulba. Circular Object Detection Using a
Modified Hough Transform. International Journal of Applied Mathematics
and Computer Science, 18(1):85-91, 2008.
[17] L A Bradshaw and J P Wikswo. Spatial filter approach for evaluation
of the surface Laplacian of the electroencephalogram and magnetoencephalogram.
Annals of Biomedical Engineering, 29(3):202-213, 2001.
[18] Nosrati Ali Nosrati Masoud, Karimi Ronak, Nosrati Hamed. A method
for detection and extraction of circular shapes from noisy images using
median filter and CHT. Journal of American Science, 7(6):84-88, 2011.
[19] B Schaffer, U Hohenester, A Trugler, and F Hofer. High-resolution
surface plasmon imaging of gold nanoparticles by energy-filtered transmission
electron microscopy. Physical Review B, 79(4):1-4, 2009.
[20] D H Ballard. Generalizing the Hough transform to detect arbitrary
shapes. Pattern Recognition, 13(2):111-122, 1981.
[21] Olivier Le Bihan, Pierre Bonnafous, Laszlo Marak, Thomas Bickel,
Sylvain Tr'epout, St'ephane Mornet, Felix De Haas, Hugues Talbot, Jean-
Christophe Taveau, and Olivier Lambert. Cryo-electron tomography of
nanoparticle transmigration into liposome. Journal of Structural Biology,
168(3):419-425, 2009.
[22] D Ioannou. Circle recognition through a 2D Hough Transform and radius
histogramming. Image and Vision Computing, 17(1):15-26, 1999.
[23] Jingyue Liu. Scanning transmission electron microscopy and its application
to the study of nanoparticles and nanoparticle systems. Journal
of Electron Microscopy, 54(3):251-278, 2005.
[24] J Illingworth and J Kittler. A survey of the hough transform. Computer
Vision Graphics and Image Processing, 44(1):87-116, 1988.
[25] Gonzalo R Arce. Nonlinear signal processing: a statistical approach.
Scientist, 48(1):0,0, 2005.
[26] Carolyn Kimme, Dana Ballard, and Jack Sklansky. Finding circles by
an array of accumulators. Communications of the ACM, 18(2):120-122,
1975.
[27] Z L Wang. Transmission Electron Microscopy of Shape-Controlled
Nanocrystals and Their Assemblies. The Journal of Physical Chemistry
B, 104(6):1153-1175, 2000.