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A hybrid approach for multiple particle tracking microrheology

Xie, Liangjun, Gu, Nong, Cao, Zhiqiang and Li, Dalong 2013, A hybrid approach for multiple particle tracking microrheology, International journal of advanced robotic systems, vol. 10, pp. 1-6, doi: 10.5772/54364.

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Title A hybrid approach for multiple particle tracking microrheology
Author(s) Xie, Liangjun
Gu, Nong
Cao, Zhiqiang
Li, Dalong
Journal name International journal of advanced robotic systems
Volume number 10
Start page 1
End page 6
Total pages 6
Publisher InTech
Place of publication Rijeka, Croatia
Publication date 2013
ISSN 1729-8806
Keyword(s) circle detection
Circular Hough Transform
multiple particle tracking
Summary Geometric object detection has many applications, such as in tracking. Particle tracking microrheology is a technique for studying mechanical properties by accurately tracking the motion of the immersed particles undergoing Brownian motion. Since particles are carried along by these random undulations of the medium, they can move in and out of the microscope's depth of focus, which results in halos (lower intensity). Two-point particle tracking microrheology (TPM) uses a threshold to find those particles with peak, which leads to the broken trajectory of the particles. The halos of those particles which are out of focus are circles and the centres can be accurately tracked in most cases. When the particles are sparse, TPM will lose certain useful information. Thus, it may cause inaccurate microrheology. An efficient algorithm to detect the centre of those particles will increase the accuracy of the Brownian motion. In this paper, a hybrid approach is proposed which combines the steps of TPM for particles in focus with a circle detection step using circular Hough transform for particles with halos. As a consequence, it not only detects more particles in each frame but also dramatically extends the trajectories with satisfactory accuracy. Experiments over a video microscope data set of polystyrene spheres suspended in water undergoing Brownian motion confirmed the efficiency of the algorithm.
Language eng
DOI 10.5772/54364
Field of Research 091007 Manufacturing Robotics and Mechatronics (excl Automotive Mechatronics)
Socio Economic Objective 861604 Integrated Systems
HERDC Research category C1 Refereed article in a scholarly journal
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Document type: Journal Article
Collection: Centre for Intelligent Systems Research
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Created: Tue, 27 Aug 2013, 12:11:05 EST

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