Digital holography with deep learning for algae identification and classification

Chinnaphat Ruttanasirawit; Suwan Plaipichit; Setthanun Thongsuwan; Pachara Thonglim; Saranya Phunpruch; Prathan Buranasiri

doi:10.1117/12.3022823

15 February 2024 Digital holography with deep learning for algae identification and classification

Chinnaphat Ruttanasirawit, Suwan Plaipichit, Setthanun Thongsuwan, Pachara Thonglim, Saranya Phunpruch, Prathan Buranasiri

Author Affiliations +

Proceedings Volume 13069, International Conference on Optical and Photonic Engineering (icOPEN 2023); 130690I (2024) https://doi.org/10.1117/12.3022823
Event: International Conference on Optical and Photonic Engineering (icOPEN 2023), 2023, Singapore, Singapore

Abstract

Recently, the characterization of marine objects, populations and biophysical interactions have become crucial within the research community. In this study, we leverage digital holographic imaging systems and deep learning networks to classify three distinct types of micro-algae: Chlamydomonas, Scenedesmus armatus, and Scenedesmus_sp-L. We employed reconstructed digital holographic images and deep learning to identify the results from both approaches. The integration of holographic imaging holds promises in replacing expensive characterization systems like AFM, x-ray diffraction, and Raman spectroscopy, offering a more costeffective solution. In our system, we utilize in-line microscopic digital holographic imaging to record and reconstruct images of the algae specimens. An essential advantage of holographic techniques is that they do not require intact samples of the specimens for effective object identification. To further enhance the process, we combined deep learning algorithms with holographic imaging, capitalizing on the advanced computers. This combination enables highly effective characterizing and classification of different types of algae. These innovative approaches pave the way for exciting advancement in marine research and monitoring.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chinnaphat Ruttanasirawit, Suwan Plaipichit, Setthanun Thongsuwan, Pachara Thonglim, Saranya Phunpruch, and Prathan Buranasiri "Digital holography with deep learning for algae identification and classification", Proc. SPIE 13069, International Conference on Optical and Photonic Engineering (icOPEN 2023), 130690I (15 February 2024); https://doi.org/10.1117/12.3022823

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