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| 001 | 837993 | ||
| 005 | 20240619083543.0 | ||
| 024 | 7 | _ | |a 10.1145/3070617.3070636 |2 doi |
| 037 | _ | _ | |a FZJ-2017-06741 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |a Kang, Kyongok |0 P:(DE-Juel1)130749 |b 0 |e Corresponding author |
| 111 | 2 | _ | |a IEEA '17 Proceedings of the 6th International Conference on Informatics, Environment, Energy and Applications |g IEEA2017 |c Jeju |d 2017-03-29 - 2017-03-31 |w South Korea |
| 245 | _ | _ | |a Image-time correlation and its applications |
| 260 | _ | _ | |c 2017 |b ACM Press New York, New York, USA |
| 295 | 1 | 0 | |a Proceedings of the 6th International Conference on Informatics, Environment, Energy and Applications - IEEA '17 - ACM Press New York, New York, USA, 2017. - ISBN 9781450352307 - doi:10.1145/3070617.3070636 |
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| 520 | _ | _ | |a In this paper, Image-time correlation is a beneficial technique to apply various applications of dynamical events, where temporal changes of positions of particles (or objects) can be quantified, constructed by the collection of time-resolved video data. With the fast development of camera technologies and imaging softwares, the optimization of time-binning and spatial-resolution are much friendly-used for the imaging analysis. Time-dependent different regions of interest (ROIs) can be chosen, such that the time resolution of subsequent images should be at least 10 times faster than the actual dynamical events. Then time-correlation function will be calculated by the 2d intensity-intensity correlation of an each pixel-pixel of individual time frame of image, and the initial slope of correlation function gives a characteristic time scale that measures the average magnitude of particle velocities within the field-of-view. The advantage of image-time correlation is easy to implement as compared to the PIV (particle imaging velocimetry). In this short proceeding, the performance of image-time correlation is highlighted through a number of applications; such as the slowing down behaviors of collective dynamics of orientation textures, dimer-oscillations in rod-networks, and clay (platelet) migrations in an oil-water droplet. In each system, the interpretation of image-time correlation is addressed, based on the experimental observations. |
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