Applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments
Abstract
Abstract In situ scanning transmission electron microscopy is being developed for numerous applications in the study of nucleation and growth under electrochemical driving forces. For this type of experiment, one of the key parameters is to identify when nucleation initiates. Typically, the process of identifying the moment that crystals begin to form is a manual process requiring the user to perform an observation and respond accordingly (adjust focus, magnification, translate the stage, etc.). However, as the speed of the cameras being used to perform these observations increases, the ability of a user to “catch” the important initial stage of nucleation decreases (there is more information that is available in the first few milliseconds of the process). Here, we show that video shot boundary detection can automatically detect frames where a change in the image occurs. We show that this method can be applied to quickly and accurately identify points of change during crystal growth. This technique allows for automated segmentation of a digital stream for further analysis and the assignment of arbitrary time stamps for the initiation of processes that are independent of the user’s ability to observe and react.
- Publication Date:
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1344022
- Grant/Contract Number:
- AC05-76RL01830
- Resource Type:
- Published Article
- Journal Name:
- Advanced Structural and Chemical Imaging
- Additional Journal Information:
- Journal Name: Advanced Structural and Chemical Imaging Journal Volume: 3 Journal Issue: 1; Journal ID: ISSN 2198-0926
- Publisher:
- Springer Science + Business Media
- Country of Publication:
- Germany
- Language:
- English
Citation Formats
Moeglein, W. A., Griswold, R., Mehdi, B. L., Browning, N. D., and Teuton, J. Applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments. Germany: N. p., 2017.
Web. doi:10.1186/s40679-016-0034-x.
Moeglein, W. A., Griswold, R., Mehdi, B. L., Browning, N. D., & Teuton, J. Applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments. Germany. https://doi.org/10.1186/s40679-016-0034-x
Moeglein, W. A., Griswold, R., Mehdi, B. L., Browning, N. D., and Teuton, J. Tue .
"Applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments". Germany. https://doi.org/10.1186/s40679-016-0034-x.
@article{osti_1344022,
title = {Applying shot boundary detection for automated crystal growth analysis during in situ transmission electron microscope experiments},
author = {Moeglein, W. A. and Griswold, R. and Mehdi, B. L. and Browning, N. D. and Teuton, J.},
abstractNote = {Abstract In situ scanning transmission electron microscopy is being developed for numerous applications in the study of nucleation and growth under electrochemical driving forces. For this type of experiment, one of the key parameters is to identify when nucleation initiates. Typically, the process of identifying the moment that crystals begin to form is a manual process requiring the user to perform an observation and respond accordingly (adjust focus, magnification, translate the stage, etc.). However, as the speed of the cameras being used to perform these observations increases, the ability of a user to “catch” the important initial stage of nucleation decreases (there is more information that is available in the first few milliseconds of the process). Here, we show that video shot boundary detection can automatically detect frames where a change in the image occurs. We show that this method can be applied to quickly and accurately identify points of change during crystal growth. This technique allows for automated segmentation of a digital stream for further analysis and the assignment of arbitrary time stamps for the initiation of processes that are independent of the user’s ability to observe and react.},
doi = {10.1186/s40679-016-0034-x},
journal = {Advanced Structural and Chemical Imaging},
number = 1,
volume = 3,
place = {Germany},
year = {2017},
month = {1}
}
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