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Información general |
| Autor |
Xie, Liangjun; Gu, Nong; Cao, Zhiqiang; Li, Dalong |
| Publicado |
InTech Open Access Publisher, 2013
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| Abstract |
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 microscopeʹs 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. |
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International Journal of Advanced Robotic Systems
Autor: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Erschienen: 2004
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