An astronomical pattern‐matching algorithm for computer‐aided identification of whale sharks Rhincodon typus
Abstract
Summary: The formulation of conservation policy relies heavily on demographic, biological and ecological knowledge that is often elusive for threatened species. Essential estimates of abundance, survival and life‐history parameters are accessible through mark and recapture studies given a sufficiently large sample. Photographic identification of individuals is an established mark and recapture technique, but its full potential has rarely been exploited because of the unmanageable task of making visual identifications in large data sets. We describe a novel technique for identifying individual whale sharks Rhincodon typus through numerical pattern matching of their natural surface ‘spot’ colourations. Together with scarring and other markers, spot patterns captured in photographs of whale shark flanks have been used, in the past, to make identifications by eye. We have automated this process by adapting a computer algorithm originally developed in astronomy for the comparison of star patterns in images of the night sky. In tests using a set of previously identified shark images, our method correctly matched pairs exhibiting the same pattern in more than 90% of cases. From a larger library of previously unidentified images, it has to date produced more than 100 new matches. Our technique is robust in that the incidence of false positives is low, while failure to match images of the same shark is predominantly attributable to foreshortening in photographs obtained at oblique angles of more than 30°. We describe our implementation of the pattern‐matching algorithm, estimates of its efficacy, its incorporation into the new ECOCEAN Whale Shark Photo‐identification Library, and prospects for its further refinement. We also comment on the biological and conservation implications of the capability of identifying individual sharks across wide geographical and temporal spans. Synthesis and applications. An automated photo‐identification technique has been developed that allows for efficient ‘virtual tagging’ of spotted animals. The pattern‐matching software has been implemented within a Web‐based library created for the management of generic encounter photographs and derived data. The combined capabilities have demonstrated the reliability of whale shark spot patterns for long‐term identifications, and promise new ecological insights. Extension of the technique to other species is anticipated, with attendant benefits to management and conservation through improved understanding of life histories, population trends and migration routes, as well as ecological factors such as exploitation impact and the effectiveness of wildlife reserves.
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Wildbook image analysis can start with images from any source and use ML and computer vision to detect multiple animals, classify their species, and identify individual animals.
“The image analysis of Wildbook can start with images from any source—scientists, camera traps, drones, community scientists, or social media—and use ML and computer vision to detect multiple animals in the images100 to not only classify their species, but identify individual animals applying a suite of different algorithms101,147.”
From Perspectives in machine learning for wildlife conservation (2022) · cites this paper as [147]
Cites
IUCN Red List of Threatened Species
(2012) · Choice Reviews Online · doi:10.5860/choice.49-6872 · Cited by 12,828 · see citing works
IUCN Red List of threatened species
(2005) · Choice Reviews Online · doi:10.5860/choice.43-2185 · Cited by 3,091 · see citing works
Schmidt, B. P., Suntzeff, N. B., Phillips, M. M., Schommer, R. A., Clocchiatti, A., Kirshner, R., Garnavich, P., Challis, P., LEIBUNDGUT, B., Spyromilio, J., et al. (1998) · The Astrophysical Journal · doi:10.1086/306308 · Cited by 1,508 · see citing works
Baillie, J., Hilton‐Taylor, C., & Stuart, S. N. (2004) · IUCN, Gland, Switzerland, and Cambridge, UK eBooks · doi:10.2305/iucn.ch.2005.3.en · Cited by 1,187 · see citing works
Springer, V. G., Last, P. R., & Stevens, J. (1994) · Copeia · doi:10.2307/1446735 · Cited by 1,168 · see citing works
2004 IUCN red list of threatened species : a global species assessment
BAILLIE, J. E. M., Hilton‐Taylor, C., & Stuart, S. N. (2004) · IUCN – The World Conservation Union eBooks · Cited by 1,038 · see citing works
Monitoring Vertebrate Populations
Davitt, B. B., Thompson, W. L., White, G. C., & Gowan, C. (1999) · Journal of Range Management · doi:10.2307/4003499 · Cited by 431 · see citing works
Sharks of the Order Carcharhiniformes
McEachran, J. D., & Compagno, L. J. V. (1989) · Copeia · doi:10.2307/1445465 · Cited by 359 · see citing works
Monitoring Vertebrate Populations
(1998) · Elsevier eBooks · doi:10.1016/b978-0-12-688960-4.x5000-x · Cited by 331 · see citing works
Willis, T. J., Millar, R. B., & Babcock, R. C. (2003) · Journal of Applied Ecology · doi:10.1046/j.1365-2664.2003.00775.x · Cited by 253 · see citing works
A pattern-matching algorithm for two-dimensional coordinate lists
Groth, E. J. (1986) · The Astronomical Journal · doi:10.1086/114099 · Cited by 153 · see citing works
Current issues with fish and fisheries: editor's overview and introduction
Ormerod, S. J. (2003) · Journal of Applied Ecology · doi:10.1046/j.1365-2664.2003.00824.x · Cited by 125 · see citing works
Hammond, P. S., Mizroch, S. A., & Donovan, G. P. (1990) · Cited by 100 · see citing works
The action plan for Australian cetaceans
Bannister, J. L., Kemper, C. M., & Warneke, R. M. (1996) · Cited by 80 · see citing works
Computer-assisted photo-identification of individual marine vertebrates: a multi-species system
Hillman, G. R., Würsig, B., Gailey, G., et al. (2003) · Aquatic Mammals · doi:10.1578/016754203101023960 · Cited by 68 · see citing works
An introduction to using mark-recapture analysis for monitoring threatened species
Lettink, M., & Armstrong, D. P. (2003) · Cited by 62 · see citing works
Norman, B. M. (1999) · Murdoch University Research Portal · Cited by 38 · see citing works
Self-citationSharks of the Order Carcharhiniformes.
Naylor, G. J. P., & Compagno, L. J. V. (1989) · Systematic Zoology · doi:10.2307/2992292 · Cited by 31 · see citing works
Query by sketch in DARWIN: digital analysis to recognize whale images on a network
Wilkin, D. J., Debure, K. R., & Roberts, Z. W. (1998) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.333870 · Cited by 7 · see citing works
Persillon, P. (2005) · International Petroleum Technology Conference · doi:10.2523/iptc-11041-abstract · Cited by 5 · see citing works
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Perspectives in machine learning for wildlife conservation
Tuia, D., Kellenberger, B., Beery, S., Costelloe, B. R., Zuffi, S., Risse, B., Mathis, A., Mathis, M. W., van Langevelde, F., Burghardt, T., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-27980-y · Cited by 740 · see citing works
Schneider, S., Taylor, G. W., Linquist, S., & Kremer, S. C. (2019) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.13133 · Cited by 245 · see citing works
Whitney, N. M., Pyle, R. L., Holland, K. N., & Barcz, J. T. (2012) · Environmental Biology of Fishes · doi:10.1007/s10641-011-9897-9 · Cited by 68 · see citing works
- Authors
- ARZOUMANIAN, Z., HOLMBERG, J., & NORMAN, B.
- Affiliations
- Goddard Space Flight Center (US)
- Murdoch University (AU)
- Corresponding author
- ARZOUMANIAN, Z.
- Venue
- Journal of Applied Ecology
- Publisher
- Wiley
- Published
- 2005-11-23
- Volume
- 42
- Issue
- 6
- Pages
- 999-1011
- ISSN
- 0021-8901 (ISSN-L)
- 1365-2664
- OpenAlex
- W1505623432
- Cited by
- 316
- References
- 20
- Citations by year
- 2026: 11 · 2025: 17 · 2024: 13 · 2023: 11 · 2022: 33 · 2021: 13 · 2020: 17 · 2019: 14 · 2018: 19 · 2017: 18 · 2016: 17 · 2015: 13 · 2014: 15 · 2013: 18 · 2012: 25
- FWCI
- 9.02
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Applied Ecology (publishedVersion)
- Murdoch University Research Portal (submittedVersion)
- Topics
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ichthyology and Marine Biology
- Physical Sciences › Environmental Science › Ecology › Marine animal studies overview
- Physical Sciences › Mathematics › Statistics and Probability › Census and Population Estimation
- Keywords
- Rhincodon typus, photo-identification, mark-recapture, population monitoring, migration routes, life history
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