Abstract
An autofocusing procedure is routinely performed under a microscope to maintain micro-objects within the depth of field of an objective lens. The aim of this procedure is to search for an optimum image with sharp edges of the outlines and features of the micro-objects by tuning the position of the objective lens. This paper describes a new robust autofocusing search algorithm based on bare-bones particle swarm optimization (BBPSO). The proposed search algorithm has been validated experimentally using sharpness analysis based on image variance.
| Original language | English |
|---|---|
| Title of host publication | 2013 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2013 |
| Pages | 213-218 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2013 |
| Event | 2013 10th IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2013 - Takamastu, Japan Duration: Aug 4 2013 → Aug 7 2013 |
Other
| Other | 2013 10th IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2013 |
|---|---|
| Country | Japan |
| City | Takamastu |
| Period | 8/4/13 → 8/7/13 |
Keywords
- Autofocus
- embryo
- image sharpness
- microscopy
- Particle swarms
ASJC Scopus subject areas
- Artificial Intelligence
- Electrical and Electronic Engineering
- Mechanical Engineering
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Cite this
Bahadur, I. M., & Mills, J. K. (2013). Robust autofocusing in microscopy using particle swarm optimization. In 2013 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2013 (pp. 213-218). [6617920] https://doi.org/10.1109/ICMA.2013.6617920