Please use this identifier to cite or link to this item: https://doi.org/10.1007/s00338-021-02101-1
Title: Development of a multi-excitation fluorescence (MEF) imaging method to improve the information content of benthic coral reef surveys
Authors: Bollati, Elena 
D’Angelo, C.
Kline, David, I
Mitchell, B. Greg
Wiedenmann, Jorg
Keywords: CCA
Chlorophyll
Functional imaging
GFP
Phycoerythrin
Survey methods
Issue Date: 6-Sep-2021
Publisher: Springer Science and Business Media Deutschland GmbH
Citation: Bollati, Elena, D’Angelo, C., Kline, David, I, Mitchell, B. Greg, Wiedenmann, Jorg (2021-09-06). Development of a multi-excitation fluorescence (MEF) imaging method to improve the information content of benthic coral reef surveys. Coral Reefs 40 (6) : 1831-1847. ScholarBank@NUS Repository. https://doi.org/10.1007/s00338-021-02101-1
Rights: Attribution 4.0 International
Abstract: Benthic surveys are a key component of monitoring and conservation efforts for coral reefs worldwide. While traditional image-based surveys rely on manual annotation of photographs to characterise benthic composition, automatic image annotation based on computer vision is becoming increasingly common. However, accurate classification of some benthic groups from reflectance images presents a challenge to local ecologists and computers alike. Most coral reef organisms produce one or a combination of fluorescent pigments, such as Green Fluorescent Protein (GFP)-like proteins found in corals, chlorophyll-a found in all photosynthetic organisms, and phycobiliproteins found in red macroalgae, crustose coralline algae (CCA) and cyanobacteria. Building on the potential of these pigments as a target for automatic image annotation, we developed a novel imaging method based on off-the-shelf components to improve classification of coral and other biotic substrates using a multi-excitation fluorescence (MEF) imaging system. We used RGB cameras to image the fluorescence emission of coral and algal pigments stimulated by narrow-waveband blue and green light, and then combined the information into three-channel pseudocolour images. Using a set of a priori rules defined by the relative pixel intensity produced in different channels, the method achieved successful classification of organisms into three categories based on the dominant fluorescent pigment expressed, facilitating discrimination of traditionally problematic groups. This work provides a conceptual foundation for future technological developments that will improve the cost, accuracy and speed of coral reef surveys. © 2021, The Author(s).
Source Title: Coral Reefs
URI: https://scholarbank.nus.edu.sg/handle/10635/232891
ISSN: 0722-4028
DOI: 10.1007/s00338-021-02101-1
Rights: Attribution 4.0 International
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